As feature subset selection and parameter tuning are important for the performance of SVM-based models, a PSO-SVM model was provided which uses particle swarm optimization (PSO) to optimize both a feature subset and parameters of SVM simultaneously so as to improve the prediction result. Finally, the PSO-SVM model was applied to a financial early warning model, which shows a better performance than the pure SVM-based model.