Predicts enzyme functional classes and subclasses. EzyPred operates by fusing the Functional Domain (FunD) approach and Pseudo Position-Specific Scoring Matrix (Pse-PSSM) approach. It first identifies a query protein as enzyme or non-enzyme. The overall success rates for the method is higher than 90%. EzyPred has been developed by fusing the results derived from the functional domain and evolution information.