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As the rapid development of wind farms, it becomes important for wind turbine monitoring and maintenance. As the operating of wind turbine, the state may change from normal to fault. The prediction of fault modes is important for the maintenance of wind turbine. In this paper, we proposed a wind turbine fault modes prediction based on a data mining method. The prediction model contains three steps:prediction of random fault; prediction of special fault; prediction of unseen fault. We chose an optimal random forest algorithm as the data mining approach based on the comparative analysis on the data collected at a large wind farm. The prediction accuracy of the model can achieve 98%, and at the same the model can predict fault modes which are not contained in the training data. Based on the practical wind turbine data, the robustness of the model is verified.