Feature selection is used for Eliminating the unnecessary features among the data and choosing the appropriate ones makes it possible to evaluate the information correctly. In this method, The Whale Optimization Algorithm, which is one of the new meta-heuristic algorithms, is used to select appropriate features. Training with artificial neural networks takes place during the evaluation process of selected features. At the end of the training, the features that provide the minimum error value are selected. In the performance evaluation of the method, known data sets will be used and the results will be given in comparison with the Particle Swarm Optimization method.