Semi-crystalline polymers are widely used in modern industry. Indeed, they are highly coveted because of their excellent compromise between advantageous mechanical properties, high lightness, good productivity and low cost. In this work, a modeling study of performance parameters such as;(Ra), (Fz), (Pc) and (MRR) was carried out using the surface response methodology (RSM). The machining operations were performed dry on two polyamides (PA66-GF30% and PA66) following the L9 (3 3 ) orthogonal array. The results were used to perform a mono-objective optimization based on the Taguchi signal-to-noise ratio (S/N). In addition, a comparative study between three multiobjective optimization methods MCDM (PSI, MABAC and MAIRCA) coupled with the Taguchi approach was realized. The target objective is to reduce (Ra, Fz and Pc) and maximize (MRR) simultaneously. The results found are original and can help researchers working in the field of machining polyamides with and without reinforcement.