This research presents the performance of Aluminum nitride ceramic in end milling using using TiAlN and TiN coated carbide tool insert under dry machining. The surface roughness of the work piece and tool wear was analyzed in this. The design of experiments (DOE) approach using Response surface methodology was implemented to optimize the cutting parameters of a computer numerical control (CNC) end milling machine. The analysis of variance (ANOVA) was adapted to identify the most influential factors on the CNC end milling process. The mathematical predictive model developed for surface roughness and tool wear in terms of cutting speed, feed rate, and depth of cut. The cutting speed is found to be the most significant factor affecting the surface roughness of work piece and tool wear in end milling process.