This study investigates the improvement of surface roughness in milling operations by incorporating SiO2 and Al2O3 nanoparticles into Minimum Quantity Lubrication (MQL). Experiments were conducted on SKD11 hardened steel using a 5-axis CNC milling machine and TiAlN-coated tungsten carbide tools. Nanoparticles of SiO2 (100nm) and Al2O3 (20nm) were mixed with synthetic oil (CT232) at a concentration of 4% wt for each. The Taguchi method was applied to optimize cutting parameters, including cutting speed, feed rate, and depth of cut. The results showed a significant reduction in surface roughness, with Al2O3 nanofluids achieving the lowest average surface roughness of 0.151 µm at optimal parameters (cutting speed: 80 m/min, feed rate: 0.01 mm/tooth, depth of cut: 0.2 mm). Analysis of variance indicated that feed rate is the most influential factor affecting surface roughness, followed by cutting conditions. The study confirms that nanoparticle-enhanced MQL outperforms conventional MQL in achieving superior surface finishes in hard milling operations, with SiO2 and Al2O3 demonstrating notable effects on surface quality. These findings offer practical insights into improving surface roughness for industrial applications, particularly in the machining of hardened steels.