This study addresses the optimization challenge of the finishing turning of SUS430C alloy material. The primary focus is on minimizing surface roughness (Ra) while simultaneously maximizing material removal rate (MRR). This approach is critical for enhancing machine efficiency and achieving superior surface quality. Utilizing the Desirability Function Approach (DFA) and Response Surface Methodology (RSM), the study delved into the effects of cutting parameters, including cutting speed (Vc), feed rate (F), and depth of cut (ap), on surface roughness (Ra) and material removal rate (MRR). The optimization process revealed that a cutting speed of 200 m/min, feed rate of 0.119 mm/min, and depth of cut of 0.200 mm predict optimal values of Ra and MRR with a high desirability index, indicating a significant improvement over the traditional method. This study not only demonstrates the efficacy of combining RSM and DFA for multi-objective optimization in machining processes but also provides a validated set of parameters that align with industrial application requirements, marking a significant contribution to the field of machining optimization.