This study investigated the machinability characteristics of the turning operation to attain the optimal combination of minimum surface roughness and the highest material removal rate. The analysis employed Response Surface Methodology (RSM). The study conducted a series of experimental runs using the Box-Behnken Design of Response Surface Methodology. The parameters of spindle speed, feed, and depth of cut were varied, while different weight percentages of reinforcements, including Al2O3 nanoparticles (at 1%, 3%, and 5% weight percentages) and Gr (at 1% weight percentage), were incorporated into the LM24 metal matrix alloy. Response Surface Methodology (RSM) analysis is carried out to optimize the turning machining parameters and enhance the machining performance for better quality and productivity. The derived optimal machining parameters have been verified through confirmatory tests. An analysis of variance (ANOVA) was used to determine the individual contributions of each parameter to the machinability characteristics. Surface morphology analysis revealed the smooth distribution of nanoparticle reinforcements to the metal matrix. The hardness and surface roughness of the machined nanocomposites were studied. Finally, the optimized output machining parameter of minimum surface roughness Ra and maximum material removal rate MRR are 0.522 μm and 110.2 mm3/sec were to be found, and the maximum hardness of the MMC composites was 60.5 HRB.