Maximum Depth of Binary Tree Last Updated : 23 Jul, 2025 Comments Improve Suggest changes Like Article Like Report Try it on GfG Practice Given a binary tree, the task is to find the maximum depth of the tree. The maximum depth or height of the tree is the number of edges in the tree from the root to the deepest node.Examples:Input: Output: 2Explanation: The longest path from the root (node 12) goes through node 8 to node 5, which has 2 edges.Input: Output: 3Explanation: The longest path from the root (node 1) to a leaf node 6 with 3 edge.Table of Content[Approach 1] Using Recursion - O(n) Time and O(h) Space[Approach 2] Level Order Traversal - O(n) Time and O(n) Space [Approach 1] Using Recursion - O(n) Time and O(h) SpaceThe idea is to recursively calculate the height of the left and the right subtrees of a node and then find height to the node as max of the heights of two children plus 1. Algorithm:If the tree is empty, return -1.Otherwise, do the following:Get the height of the left subtree recursively, i.e., call height(node->left).Get the height of the right subtree recursively, i.e., call height(node->right).Compute the maximum of the heights of the left and right subtrees and add 1 to it for the current node.height = max(height of left subtree, height of right subtree) + 1.Return the height. C++ #include <iostream> using namespace std; class Node { public: int data; Node *left; Node *right; Node(int val) { data = val; left = nullptr; right = nullptr; } }; // Returns height which is the number of edges // along the longest path from the root node down // to the farthest leaf node. int height(Node *root) { if (root == nullptr) return -1; // compute the height of left and right subtrees int lHeight = height(root->left); int rHeight = height(root->right); return max(lHeight, rHeight) + 1; } int main() { // Representation of the input tree: // 12 // / \ // 8 18 // / \ // 5 11 Node *root = new Node(12); root->left = new Node(8); root->right = new Node(18); root->left->left = new Node(5); root->left->right = new Node(11); cout << height(root); return 0; } C #include <stdio.h> #include <stdlib.h> struct Node { int data; struct Node* left; struct Node* right; }; // Returns "height" which is the number of edges // along the longest path from the root node down // to the farthest leaf node. int height(struct Node* root) { if (root == NULL) return -1; // compute the height of left and right subtrees int lHeight = height(root->left); int rHeight = height(root->right); return (lHeight > rHeight ? lHeight : rHeight) + 1; } struct Node* createNode(int val) { struct Node* node = (struct Node*)malloc(sizeof(struct Node)); node->data = val; node->left = NULL; node->right = NULL; return node; } int main() { // Representation of the input tree: // 12 // / \ // 8 18 // / \ // 5 11 struct Node* root = createNode(12); root->left = createNode(8); root->right = createNode(18); root->left->left = createNode(5); root->left->right = createNode(11); printf("%d\n", height(root)); return 0; } Java class Node { int data; Node left, right; Node(int val) { data = val; left = null; right = null; } } class GfG { // Returns height which is the number of edges // along the longest path from the root node down // to the farthest leaf node. static int height(Node root) { if (root == null) return -1; // compute the height of left and right subtrees int lHeight = height(root.left); int rHeight = height(root.right); return Math.max(lHeight, rHeight) + 1; } public static void main(String[] args) { // Representation of the input tree: // 12 // / \ // 8 18 // / \ // 5 11 Node root = new Node(12); root.left = new Node(8); root.right = new Node(18); root.left.left = new Node(5); root.left.right = new Node(11); System.out.println(height(root)); } } Python class Node: def __init__(self, val): self.data = val self.left = None self.right = None # Returns height which is the number of edges # along the longest path from the root node down # to the farthest leaf node. def height(root): if root is None: return -1 # compute the height of left and right subtrees lHeight = height(root.left) rHeight = height(root.right) return max(lHeight, rHeight) + 1 if __name__ == "__main__": # Representation of the input tree: # 12 # / \ # 8 18 # / \ # 5 11 root = Node(12) root.left = Node(8) root.right = Node(18) root.left.left = Node(5) root.left.right = Node(11) print(height(root)) C# using System; class Node { public int data; public Node left, right; public Node(int val) { data = val; left = null; right = null; } } class GfG { // Returns height which is the number of edges // along the longest path from the root node down // to the farthest leaf node. static int height(Node root) { if (root == null) return -1; // compute the height of left and right subtrees int lHeight = height(root.left); int rHeight = height(root.right); return Math.Max(lHeight, rHeight) + 1; } static void Main(string[] args) { // Representation of the input tree: // 12 // / \ // 8 18 // / \ // 5 11 Node root = new Node(12); root.left = new Node(8); root.right = new Node(18); root.left.left = new Node(5); root.left.right = new Node(11); Console.WriteLine(height(root)); } } JavaScript class Node { constructor(val) { this.data = val; this.left = null; this.right = null; } } // Returns height which is the number of edges // along the longest path from the root node down // to the farthest leaf node. function height(root) { if (root === null) { return -1; } // compute the height of left and right subtrees let lHeight = height(root.left); let rHeight = height(root.right); return Math.max(lHeight, rHeight) + 1; } // Driver Code // Representation of the input tree: // 12 // / \ // 8 18 // / \ // 5 11 let root = new Node(12); root.left = new Node(8); root.right = new Node(18); root.left.left = new Node(5); root.left.right = new Node(11); console.log(height(root)); Output2Below is the illustration of above approach:Example: Consider the following tree - height(’12’) = max(height(‘8′), height(’18’)) + 1 = 1 + 1 = 2because recursively:height(‘8’) = max(height(‘5′), height(’11’)) + 1 = 0 + 1 = 1height(’18’) = max(height(NULL), height(‘NULL’)) + 1 = (-1) + 1 = 0height(“5”) = max(height(NULL), height(‘NULL’)) + 1 = (-1) + 1 = 0height(“11”) = max(height(NULL), height(‘NULL’)) + 1 = (-1) + 1 = 0[Approach 2] Level Order Traversal - O(n) Time and O(n) Space If we take a closer look at the breadth first traversal, we can notice that after we process the last node of the current level, the queue contains all the nodes of next level. This is true from the root (or first level) So we get the size of the queue in a loop to count the nodes of every level. Algorithm:Initialize an empty queue q to store nodes of the tree and a variable depth to keep track of the number of levels.Push the root node into the queue q.While the queue is not empty:Store the number of nodes at the current level as levelSize (the size of the queue).For each node in the current level (loop from 0 to levelSize):Dequeue the front element from the queue (i.e., process the node).If the node has a left child, enqueue it.If the node has a right child, enqueue it.After processing all nodes at the current level, increment the depth.Return depth - 1 as the number of edges encountered will be one less than number of nodes. C++ #include <iostream> #include <queue> using namespace std; class Node { public: int data; Node *left, *right; Node(int val) { data = val; left = nullptr; right = nullptr; } }; int height(Node* root) { if (!root) return 0; // Initializing a queue to traverse // the tree level by level queue<Node*> q; q.push(root); int depth = 0; // Loop until the queue is empty while (!q.empty()) { int levelSize = q.size(); // Traverse all nodes at the current level for (int i = 0; i < levelSize; i++) { Node* curr = q.front(); q.pop(); if (curr->left) q.push(curr->left); if (curr->right) q.push(curr->right); } // Increment depth after traversing each level depth++; } return depth - 1; } int main() { // Representation of the input tree: // 12 // / \ // 8 18 // / \ // 5 11 Node *root = new Node(12); root->left = new Node(8); root->right = new Node(18); root->left->left = new Node(5); root->left->right = new Node(11); cout << height(root); return 0; } Java import java.util.LinkedList; import java.util.Queue; class Node { int data; Node left, right; Node(int val) { data = val; left = null; right = null; } } class GfG { static int height(Node root) { if (root == null) return 0; // Initializing a queue to traverse // the tree level by level Queue<Node> q = new LinkedList<>(); q.add(root); int depth = 0; // Loop until the queue is empty while (!q.isEmpty()) { int levelSize = q.size(); // Traverse all nodes at the current level for (int i = 0; i < levelSize; i++) { Node curr = q.poll(); if (curr.left != null) q.add(curr.left); if (curr.right != null) q.add(curr.right); } // Increment height after traversing each level depth++; } return depth - 1; } public static void main(String[] args) { // Representation of the input tree: // 12 // / \ // 8 18 // / \ // 5 11 Node root = new Node(12); root.left = new Node(8); root.right = new Node(18); root.left.left = new Node(5); root.left.right = new Node(11); System.out.println(height(root)); } } Python from collections import deque class Node: def __init__(self, data): self.data = data self.left = None self.right = None # Function to find the height of the tree def height(root): if root is None: return 0 # Initializing a queue to traverse # the tree level by level q = deque([root]) depth = 0 # Loop until the queue is empty while q: levelSize = len(q) # Traverse all nodes at the current level for _ in range(levelSize): curr = q.popleft() if curr.left: q.append(curr.left) if curr.right: q.append(curr.right) # Increment depth after traversing each level depth += 1 return depth - 1 if __name__ == "__main__": # Representation of the input tree: # 12 # / \ # 8 18 # / \ # 5 11 root = Node(12) root.left = Node(8) root.right = Node(18) root.left.left = Node(5) root.left.right = Node(11) print(height(root)) C# using System; using System.Collections.Generic; class Node { public int data; public Node left, right; public Node(int x) { data = x; left = null; right = null; } } class GfG { static int height(Node root) { if (root == null) { return 0; } // Initializing a queue to traverse // the tree level by level Queue<Node> q = new Queue<Node>(); q.Enqueue(root); int depth = 0; // Loop until the queue is empty while (q.Count > 0) { int levelSize = q.Count; // Traverse all nodes at the current level for (int i = 0; i < levelSize; i++) { Node curr = q.Dequeue(); if (curr.left != null) { q.Enqueue(curr.left); } if (curr.right != null) { q.Enqueue(curr.right); } } // Increment depth after traversing // a level depth++; } return depth - 1; } static void Main(string[] args) { // Representation of the input tree: // 12 // / \ // 8 18 // / \ // 5 11 Node root = new Node(12); root.left = new Node(8); root.right = new Node(18); root.left.left = new Node(5); root.left.right = new Node(11); Console.WriteLine(height(root)); } } JavaScript class Node { constructor(data) { this.data = data; this.left = null; this.right = null; } } // Function to find the height of the tree function height(root) { if (root === null) { return 0; } // Initializing a queue to traverse // the tree level by level let queue = [root]; let depth = 0; // Loop until the queue is empty while (queue.length > 0) { let levelSize = queue.length; // Traverse all nodes at the current level for (let i = 0; i < levelSize; i++) { let curr = queue.shift(); if (curr.left) { queue.push(curr.left); } if (curr.right) { queue.push(curr.right); } } // Increment depth after traversing a level depth++; } return depth - 1; } // Representation of the input tree: // 12 // / \ // 8 18 // / \ // 5 11 let root = new Node(12); root.left = new Node(8); root.right = new Node(18); root.left.left = new Node(5); root.left.right = new Node(11); console.log(height(root)); Output2 Height of a Binary Tree Visit Course Height of a Binary Tree Maximum Depth or Height of Binary Tree Comment More infoAdvertise with us Next Article Analysis of Algorithms K kartik Follow Improve Article Tags : Tree DSA Trees Height of a Tree Amazon VMWare Cadence India Snapdeal Zoho MakeMyTrip Synopsys tree-traversal Monotype Solutions CouponDunia FreeCharge FactSet Teradata +13 More Practice Tags : AmazonCadence IndiaCouponDuniaFactSetFreeChargeMakeMyTripMonotype SolutionsSnapdealSynopsysTeradataVMWareZohoTree +9 More Similar Reads Basics & PrerequisitesLogic Building ProblemsLogic building is about creating clear, step-by-step methods to solve problems using simple rules and principles. 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