A series of experiments aimed to generate and learn fuzzy models for the valuation of residential premises was conducted using the KEEL tool (knowledge extraction based on evolutionary learning). Four regression and four post-processing algorithms were applied to several data sets. They referred to sales/purchase transactions of residential premises, which were derived from the cadastral system and the registry of real estate transactions. The results proved the usefulness of the tool to carry out laborious and tedious investigation in a relatively short time. Further research is needed to determine to what extent data coming from such sources allow to build the real estate valuation models.