The applications of cutting fluids in metal cutting have negative results such as increasing machining cost and polluting environment, water and soil pollution stemming from wastes. Therefore, use of Minimum Quantity Lubrication (MQL) technique is generally preferred since it not only gives better results but also exhibits favorable influences on environmental pollution and human health. The objective of this experimental and statistical study is to investigate the effects of both machining conditions (MQL, Dry and Wet) and cutting parameters on sustainability and machinability. Another aim of this study is to establish significance of control factors on the response values by using signal to noise (S/N) ratio, Taguchi orthogonal array, analyses of variance (ANOVA), linear and quadratic equations and to select optimal cutting parameters as well. Also, the Pugh matrix approach was utilized to compare different coolant types in terms of sustainable manufacturing. According to the experimental results, it was found that MQL cutting significantly decreased cutting tool wear when compared to dry and wet cutting, while it reduced main cutting force (Fc) and surface roughness (Ra) in general. The results of S/N ratios showed that MQL had more significant effect on Ra and Fc than wet and dry cutting. The values of optimal cutting condition were obtained as 0.16 mm/rev and 125 m/min for feed rate and cutting speed in MQL machining, respectively. According to the experimental results, it was found that MQL cutting, when compared dry and wet cutting, decreased by average 25%dry, 5%wet, 15%dry, 2%wet, 44%dry and 9%wet in terms of cutting tool wear, Fc and Ra, respectively. According to ANOVA, feed rate is the most effective factor on Fc and Ra values. It was found that the results estimated for Fc and Ra values using Taguchi method, linear and quadratic equations are quite successful within 3% deviation. According to Pugh matrix approach assessment results, MQL machining was superior to dry and wet machining in terms of sustainability and cleaner production.