More than 380,000 hips are replaced with total joint prostheses each year in the U.S. Wear debris generated by metal-on-metal implant designs is of concern due to potential adverse biological effects arising from chronic exposure of human tissue to the wear debris. This paper presents a new methodology for optimizing the wear performance of prosthesis made of Co-Cr-Mo alloys by varying tool edge geometry and machining conditions to alter the wear behavior of this alloy, while also controlling the residual stresses induced during the machining process. The machining process causes inhomogeneous inelastic deformations near the surface layer of machined parts which create residual stresses in the surface of machined components. Residual stresses in the machined surface and the subsurface are affected by cutting tool material, tool geometry, workpiece, tool-work interface conditions, and the cutting parameters such as feed rate, depth of cut and cutting speed. In the current work, residual stresses were measured using X-ray diffraction technique (XRD). The surface residual stresses in two directions (radial and hoop) were measured on the machined pins after machining with different machining conditions, but prior to the wear test. Wear behavior of Co-Cr- Mo alloy pin specimens, produced from machining with varying tool edge geometry and machining conditions, was studied using a custom-made biaxial motion pin-on-disc tribological testing system in which the pin specimen is immersed in a simulated bio-fluid environment. Wear-induced weight loss (± 10 μg) and changes in surface roughness (± 0.001 μm) were obtained at 100,000 cycle intervals upto 500,000 cycles. Metallographic analysis was performed on the machined pin specimens to analyze the microstructure and microhardness before and after testing. The rate of wear for the specimens was lowest for those pins where the change of the subsurface microhardness was small due to prevention of additional steady state wear after the initial run-in wear in the wear tester. A combination or response surface methodology and genetic algorithm (GA) was used in to optimize the various machining parameters for minimized wear generation. The optimal combination of the four machining parameters (feed 0.18mm/rev, nose radius 0.6 mm, cutting speed 27.6 m/min and depth of cut 0.38) produced the largest compressive residual stresses on the surface and subsurface of the implants thereby reducing the wear/debris generation by about fifty percent.