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Machining of advance aerospace materials like alloys of aluminum has posed a lot of challenges with the existing cutting tools higher the metal feed cutting rate lower is the surface finish and lower is metal feed cutting rate better is the surface finish. Also surface finish has played a prominent role in the machining of materials as it determines the number of steps required for process of aluminum alloy from the initial stage i.e. raw material stage to finished product. The experimental investigation was conducted by varying different operating parameters like spindle speed, feed rate and depth of cut. The obtained results were taken as inputs and by using Artificial Neural Network to obtain optimized solution of different conflicting parameters in terms of higher feed rate, maximum depth of cut and higher spindle speed accompanied by best surface finish.