The most vital phenomenon in machining is optimization, as it defines the continuous improvement in the quality of the material. Cutting fluid becomes, nowadays, an important part of turning because it assists to minimize the mechanical and thermal losses. Minimization of Chip Reduction Coefficient and optimization of the cutting parameters contribute to protect losses of productivity and to reduce the production cost. This work investigates the optimized cutting parameters in dry turning and wet turning of AISI 201 stainless steel work piece using cemented carbide tool and finds the minimum chip reduction coefficient and compares the results of the two conditions. It reveals that the cutting fluid shows a significant effect on the machining and reduces the chip reduction coefficient. Statistical analysis ANOVA shows that Depth of Cut and Spindle speed is the most influential factor in wet and dry turning respectively. It uses Multiple Regressions to predict the output and to find the correlation between parameters. Genetic Algorithm is used to select the optimal values of cutting parameters and find the minimized Chip Reduction Coefficient. The optimized cutting parameters from Genetic Algorithm for both dry and wet turning are spindle speed of 650 rev/min, feed rate of 0.12 mm/rev and depth of cut of 0.4 mm. The minimum chip reduction coefficient for dry turning is 1.067651 and for wet turning is 1.020852.