The current research deals with Taguchi-coupled grey relational analysis (GRA) multiobjective optimization of wire electric discharge machining (WEDM) for better surface roughness (Ra) and the material removal rate (MRR) over magnesium/halloysite nano tube/zirconium (Mg/HNT/Zr) metal matrix composite (MMC). Hybrid composites are created through the powder metallurgy route by varying the weight percentage of reinforcements HNT (5 and 10%) and Zr (0.5 and 1%) to the weight of the base material magnesium. Machining is carried out by varying the factors such as reinforcement’s weight percentage, pulse OFF time, pulse ON time, and wire feed (WF) based on Taguchi’s L27 orthogonal array. The response surface roughness (Ra) and the material removal rate (MRR) were studied through Taguchi-coupled GRA to evaluate the optimized machining parameters. ANOVA results reveal the percentage contribution of certain factors over the machining of composites. The developed regression model proved that the predicted values were merely similar to the experimental values of MRR and Ra. The best parametric combinations obtained from optimization are inline as the minimum weight percentage of reinforcements, and higher Pon, higher WF, and the lowered Poff are used to attain the best rate of MRR during machining and for minimized surface roughness.