In this study, the rotor torque of wind turbines has been predicted using machine learning approach based on real time data which have been collected for the designed small scale Savonius and four leaves rotors. The tip speed ratio (TSR) has been selected as the main input parameter in machine learning modelling technique which are linear regression (LR), support vector machine (SVM) regression and Gaussian process (GP) regression. The hyperparameter of these models have been defined by grid search method. RMSE, determination coefficient, MSE and MAE have been used to evaluate the predictive performance of the models to experimental data. The rotor torque modelling results show the efficiency of wind turbines can be maximized with high estimation accuracy of models. On the other hand, it has been also observed that torque of the Savonius type wind turbine is higher than the four leaves turbine