Aluminum bronze alloy machining is economically prominent and it is prevalently applied in the majority of industries like automotive, aeronautics, army and nuclear sectors. Therefore, it is worth to accurately specify the influence of different parameters on process outputs using algorithmic methods and advanced analytical approaches to achieve a work-piece with desirable features. In this study, for the first time, the effect of machining parameters namely rotational speed, feed rate and depth of cut on surface roughness of the workpiece was examined using response surface method. Implying a linear second order regression model, the effect of each individual parameter was studied. Moreover, using Sobol sensitivity analysis the sensitivity of surfacequality to each of the model inputs was considered. Then using Dringer algorithm the optimization of the process was followed. The optimized combination of parameters was feed rate of 0.1 mm/rev, rotational speedof 1400 rpm and depth of cut of 2.5 mm. Maximum sensitivity of surface roughness refers to feed rate with 88.6% of effect and after that depth of cut and rotational speed stand with 6.8% and 4.5% of effect respectively.