Rapid prediction of hepatic clearance for drug candidates plays an important role for decision-making in the early drug-discovery stage. Although knowledge of protein binding in both plasma and microsomal components is needed in the prediction of metabolic clearance from metabolic stability studies, the capacity of protein binding assays are generally lower than those of metabolic stability assays. However, many in silico prediction methods for protein binding are now available and software packages such as ACDLabs®, ADMET Predictor® and SimCYP® incorporate various aspects of in silico predictions relevant to estimating binding and clearance. This has facilitated the use of various estimated or measured physicochemical parameters, relevant to binding, to predict clearance. In this study, prediction of protein binding for 33 drugs was evaluated using various combinations of estimated physicochemical properties. Subsequently, the most accurate estimated protein binding values were used to predict hepatic clearance using the SimCYP® software. For the drugs used herein, SimCYP® provided the most accurate prediction for protein binding in both plasma and microsomes using physiochemical properties estimated with the ACDLabs software®. In conclusion, the use of in silico methods as an integrated part of predicting hepatic clearance in early drug-discovery stage is recommended.