High speed turning (HST) is an approach that can be used to increase the material removal rate (MRR) by higher cutting speed. Increasing MRR will lead to shortening time to market. In contrast, increasing the cutting speed will lead to increasing the flank wear rate and then the tooling cost.  However, the main factor that will justify the best level of cutting speed is the tooling cost which merges all in one understandable measurable factor for manufacturer. The aim of this paper is to determine experimentally the optimum cutting levels that minimize the tooling cost in machining AISI 304 as a work piece machined by a coated carbide tool using one of the non-conventional methods: Genetic Algorithm (GA). The experiments were designed using Box Behnken Design (BBD) as part of Response Surface Methodology (RSM) with three input factors: cutting speed, feeding speed and depth of cut.