Optimization is a mathematical model for finding and identifying the best possibility from a collection of alternatives. The study provides a predictive model which correlates the input and output variables in Electric Discharge machining(EDM) process by using four input parameters Ip (Pulse current), Ton(Pulse on time), Tau and V (Gap voltage) and two main outputs as Surface Roughness(Ra) and Material removal rate(MRR). The quality and performance of the finished product is tested through its Surface roughness. So importance is given to minimize the surface roughness. It is always desirable that the finished product need not be further grinded or polished. To acquire the desired optimum level of surface roughness, we need to select machining parameters in EDM. A set of operations to take away the undesired excess material to get the desired shape is the material removal process. In this experiment, D2 steel is used to achieve the minimum surface roughness and maximum material removal rate. A regression model was developed through RSM approach to predict average Surface roughness and Material Removal Rate. Further Genetic algorithm is used to predict the maximum MRR and minimum Surface roughness. © 2016, International Journal of Pharmacy and Technology. All rights reserved.