In machining of parts, surface quality is one of the most specified customer requirements. Major indication of surface quality on machined parts is surface roughness. There are various machining parameters which have an effect on the surface roughness, but these effects have not been adequately quantified. In order for manufacturers to maximize their gains from utilizing finish hard turning, accurate predictive models for surface roughness and tool wear must be constructed. This paper utilizes response surface methodology (RSM) for modeling to predict surface roughness and tool wear for variety of cutting conditions in finish hard turning. The experimental data obtained from performed experiments in finish turning of hardened AISI H-11 steel have been utilized. Decrease in feed rate and increase in cutting speed resulted in significant increase in surface quality. However, increase in cutting speed also produced relatively higher tool wear. Also depth of cut did not significantly affect the tool wear and surface roughness.