This study investigates and optimizes the machining parameters of the CNC end milling process applied to mild steel workpieces, with a focus on surface roughness measurements. Traditional approaches typically assess surface roughness post-machining, but this research employs Response Surface Methodology (RSM) to analyze the impact of critical milling parameters—spindle speed (N), depth of cut (d), and feed rate (f)—on surface finish. The experimental work was conducted using Minitab 18 software, and response optimization techniques were utilized through Regression Analysis (RA) to determine the optimal process parameters. The optimized parameters identified include a spindle speed of 2000 m/min, a feed rate of 700 mm/pass, and a depth of cut of 0.1 mm, which achieved a minimum surface roughness of 1.64256 μm. The proposed model demonstrated an accuracy of over 80% in fitting the investigated values, indicating its effectiveness in identifying optimal conditions and enhancing milling process efficiency.