Ceramic particle-reinforced aluminum matrix composites are gaining attention especially from the automotive and aerospace industry requiring light-weight and high-strength materials for various applications. Since the AlB2 reinforced composites are relatively new materials, there is no investigation into the machinability of such materials in the literature. Therefore, the aim of this paper is to study machinability of AlB2/Al-Mg-3 composite materials to optimize cutting force and surface roughness during turning operation. Taguchi's statistical approach has also been utilized for the optimization of the process parameters. The optimum conditions providing the lowest cutting force and surface roughness were estimated. For the experimental planning, L-8 (2(7)) orthogonal array and the smaller-the-better response criterion were selected to obtain optimum conditions. Analysis of variance was used to determine the most significant parameters affecting the cutting force and surface roughness generated. The optimum condition was predicted from the combination of following factors and their respective levels; the second level of material type (AlB2/Al-Mg-3), first level of cutting tool (TiN coating), first level of feed rate (0.08 mm/rev) and first level of cutting speed (350 m/min). Confirmation tests were performed to determine the effectiveness of Taguchi's optimization method using the optimal levels of test parameters. A good agreement with a confidence level of 99.5% has been observed between the predicted and tests results for both cutting force and surface roughness.