Iron ore is an important raw material for the steel industry, so it is of great economic significance to determine the grade of the iron ore quickly and accurately. And the TFe content is the main indicator that determines the grade of the iron ore and whether the iron ore can be smelted directly. Unlike manual methods and methods for chemical analysis, the paper uses the selection of band for the near‐infrared spectrum based on the pruning method and the two‐hidden‐layer extreme learning machine based on LU decomposition and seagull optimization algorithm (LU‐TELM‐SOA) to identify the TFe content. First of all, the paper proposes the selection of band based on the pruning method to retain the sensitive band of the near‐infrared spectrum. Aiming at the problems of poor stability and low accuracy of a single LU‐TELM (the two‐hidden‐layer extreme learning machine based on LU decomposition) model, the paper proposes LU‐TELM‐SOA. The experimental results show that LU‐TELM‐SOA has the advantages of high accuracy and strong stability.