The first-principle, quantitative structure–hepatic clearance relationship for 50 drugs was constructed based on selected molecular descriptors calculated by TSAR software. The R 2 of the predicted and observed hepatic clearance for the training set (n=36) and test set (n=13) were 0.85 and 0.73, respectively. The average fold error (AFE) of the in silico model was 1.28 (n=50). The prediction accuracy of in silico model was superior to in vitro hepatocytes' model in literature (n=50, AFE=2.55). It is attractive to predict human hepatic clearance based on molecular descriptors merely. The structure-based model can be used as an efficient tool in the rapid identification of hepatic clearance of new drug candidates in drug discovery.