Research is prepared for CNC-turning method, so for this purpose certain parameters, which are the most common utilized, have been chosen. Essential, for proper machining, with the minimization of production costs, these parameters have to be considered essentials. As for input parameters, cutting or also known as surface speed vc has been stated in m/min, feederate f in mm/rev, and cutting depth ap, which is given in mm. As these parameters have been included as input, the particle swarm algorithm requires for its optimizing purposes corresponding outputs, on their basis, we can acquire optimal or near optimal equations, that can be used for optimal machining processes. Output parameters have been chosen by distinct parameters which are essential by turning. Main cutting force FC is given in N, surface roughness Ra in μm and maximal tool life T in min. Utilizing these parameters, including distinct optimizing polynoms we can achieve by regression analysis optimization through particle swarm optimization approach. For research purposes, 20 single tests have been made, for both rough and fine machining. For each individual test new cutting insert has been used, since tool life has also been measured. Tests have been conducted by Jurkovic Z. for the purpose of genetic programming optimization algorithm [6].