In development and application of wind energy, for improving the prediction accuracy of wind power output, a prediction model based on improved optimal foraging algorithm for support vector machine（IOFA-SVM） is proposed. Cauchy variation and differential mutation strategy are added into the traditional optimal foraging algorithm to improve the global optimization ability to obtain the optimal parameters of SVM. Using the improved IOFA-SVM model to predict wind power output and comparing the results with BP, GWO-SVM and OFA-SVM models, the three evaluation indexes MAE, NMAE and NRMSE of the model decreased by 0.59%, 0.53% and 0.50% respectively, which shows that the IOFA-SVM model does improve the precision and accuracy of wind power output prediction, and is important to dispatch electric energy and maintain power grid stability.