Abstract: This study focuses on the multi-objective optimization of drilling parameters—specifically feed and spindle speed—for chopped glass fiber reinforced polyester (CGFRP) composites with varying fiber volume fractions. To enhance machining efficiency, drilled hole quality, and energy performance, key output metrics, including material removal rate (MRR), delamination size, thrust force, and drilling torque, were evaluated. A hybrid optimization technique integrating Grey Relational Analysis (GRA) with Principal Component Analysis (PCA) was employed to systematically balance and improve these performance indicators, supporting a more sustainable drilling process. Analysis of variance (ANOVA) is used to determine the most influential parameters for machinability properties, delamination size, and grey relational grade (GRG). Results revealed the feed as the most influential control factor on weighted GRGw. The optimum drilling parameters for the multi-objective optimization were a feed of 0.08 mm/r for all fiber volume fractions in the composite and a spindle speed ranging from 875 to 1850 rpm as fiber volume fractions ranged from 0.16 to 0.27.