Particle-filled polymer composites have become attractive because of their wide applications and low cost. Carbon fiber reinforced polymer (CFRP) is well known as a difficult-to-cut material, which has very strong physical and mechanical characteristics. Machining of carbon fiber reinforced composites is essential to have functional upshots, out of which drilling is the key operation needed for fabrication. In this paper Taguchi L-27 experimental design is coupled with grey relational analysis (GRA) to optimize the multiple performance characteristics in the drilling of fly ash-filled carbon fiber reinforced composites. Experiments were conducted on a vertical machining center, and Taguchi L-27 experimental design was chosen for the experiments. The drilling parameters, namely spindle speed, feed rate, drill diameter and wt% of fly ash, have been optimized based on the multiple performance characteristics including thrust force, surface roughness, and delamination. The GRA with multiple performance characteristics indicates that the wt% of fly ash and drill diameter are the most significant factors that affect the performance. Experimental results have shown that the performance in the drilling process can be improved effectively by using this approach.