Electrochemical machining (ECM) is one of the important non-traditional machining processes, which is used for machining of difficult-to-machine materials and intricate profiles. Being a complex process, it is very difficult to determine optimal parameters for improving cutting performance. Metal removal rate and surface roughness are the most important output parameters, which decide the cutting performance. There is no single optimal combination of cutting parameters, as their influences on the metal removal rate and the surface roughness are quite opposite. A multiple regression model was used to represent relationship between input and output variables and a multi-objective optimization method based on a non-dominated sorting genetic algorithm-II (NSGA-II) was used to optimize ECM process. A non-dominated solution set was obtained.