Purpose/SignificanceTo study a partial least squares (PLS) screening method for traditional Chinese medicine (TCM) pharmacological substances based on the minimum root mean square error (RMSE) criterion,in order to observe and analyze the action mechanism of traditional Chinese medicine comprehensively. Method/Process The main objective is to obtain the variable importance in the projection (VIP) values of features using the PLS method with the minimum RMSE as the main criteria. Then the importance of features is ranked based on the VIP values. Finally, by using PLS regression and forward search methods, the feature subset is determined based on the criteria of the minimum RMSE and obtaining the best cross validation results. Experimental data on the treatment of acute pancreatitis with the combination of DaChengQi Tang and MaXingShiGan Tang for cough, asthma, and fever are verified. Result/Conclusion This method can obtain the minimum residual and subset of pharmacological substances with the best regression performance. Features with a VIP value greater than 1 are relatively important, and features with a VIP value less than 1 may also have an impact on the model performance.