The present work focuses on the performance modeling of hard milling to attain an optimum parameter setting for the minimum cutting force and surface roughness. Furthermore, it was attempted to compute the minimum quantity lubricant flow rate precisely, besides the cutting speed and table feed rate, by adopting Grey-based Taguchi method and composite desirability function. The experimental data was collected by end milling of hardened AISI 4140 steel using carbide cutter under dry and minimum quantity lubrication conditions according to Taguchi L (16) orthogonal array. The predictive model of the responses was formulated by using response surface methodology. The analysis of variance revealed that the table feed has the maximum influence on cutting force, and the flow rate of lubricant has the highest effect on surface roughness. The parameter setting at lower table feed, higher cutting speed, and 150-ml/h lubricant flow yield the minimum value of the responses. Finally, the results of confirmation test verified the adequacy and supremacy of the optimization models; however, Grey-based Taguchi method induced a better optimization.