Individual credit risk evaluation has played an extremely important role in the credit risk management of commercial banks. Firstly, through Logistic regression, this paper selects and determines the clustering factors. Then the bilateral clustering structure is proposed. Based on the clustering structure, we cluster to the test samples, and distinguish the individual credit risk as well. Finally, we use the ROC method to test the proposed model and Logistic regression model. The results of comparison show that the discrimination method of individual credit risk based on bilateral clustering can better identify the risk.