The aim of the present research focuses on the prediction of machining parameters that improve the quality of the surface finish. The surface roughness is one of the important properties of workpiece quality in the CNC turning process. An effective approach of optimization techniques “ANN tool on MATLAB” and Response surface methodology has been implemented.T he factors investigated was spindle speed, feed rate and depth of cut. The parameters that affect the turning operation are vibration, tool wear, surface roughness, etc. Among this surface roughness is an important factor that affects the quality of the manufacturing process. The main objective of this report is to predict the surface roughness on AA 3003, by optimizing the input parameters such as spindle speed, feed rate and depth of cut by using carbide tool. A second order mathematical model is developed using “Taguchi method and optimization of surface roughness using ANN tool on MATLAB for response surface methodology.” The experimental results indicate that the proposed mathematical models suggested could adequately describe the performance indicators within the limits of the factors that are being investigated. The feed rate is the most significant factor that influences the surface roughness and however, there are other factors that provide secondary contributions to the performance indicators. Therefore, this study attempts the application of response surface methodology and “ANN tool on MATLAB” to find the optimal solution of the cutting conditions for giving the minimum value of surface roughness.