Abstract: Personal credit scoring plays all important role for commercial banks to control consumer credit risks． Aiming at the low predictive accuracies of single models，this paper presents a combining forecast model for personal credit scoring．Based on two single statistical models of linear regression and logistic regression，this paper constructs a non．hnear combining forecast based on genetic programming(GP)and uses the constructed model to classify the consum— er credit data of one commercial bank．The application results indicate that tIIe non—linear combining forecast based on GP increases the predictive accuracy effectively and the model also gets a much lower typeⅡerror rate which is more印一 pheable for commercial banks to control consumer credit risks．