Computer models for the prediction of nephrotoxicity of small mol. drugs were established.Totally 876 small mol. drugs were collected from side effect resource (SIDER) database.Of these drugs 344 had adverse reactions related to nephrotoxicity, and the remaining drugs had no adverse reactions of nephrotoxicity.The predicting models by k-nearest neighbor (KNN) and support vector machine (SVM) were established based on calculation and selection of 2D descriptors.Twenty-two compounds from traditional Chinese medicines (TCM) were used as a test set to evaluate the prediction accuracy of the models.The KNN model, if k=1, had better accuracy for the training set itself, and also had the highest accuracy of 64.29% for the test set.The SVM model had an accuracy of 80.25% for the training set, but had a low accuracy, only 45.45%, for the test set.The KNN model of k=1 can predict the nephrotoxicity of 22 TCM compounds with reasonable accuracy.