The influence of cutting parameters on surface roughness in face milling has been examined. Cutting speed, feed rate and depth of cut have been taken into consideration as the influential factors. A series of experiments have been carried out in accordance with a design of experiment (DOE). In order to obtain mathematical models that are able to predict surface roughness two different modeling approaches, namely regression analysis and neural networks, have been applied to experimentally determined data. Obtained results have been compared and neural network model gives better explanation of the observed physical system. Optimal cutting parameters have been found using simplex optimization algorithm.U ovom radu istražen je utjecaj parametara obrade (brzina rezanja, posmak i dubina rezanja) na hrapavost obrađene površine pri čeonom glodanju. Obavljen je niz pokusa u skladu sa planom eksperimenta. U cilju dobivanja matematičkog modela kojim se može predvidjeti hrapavost obrađene površine, eksperimentalni podaci obrađeni su metodologijom regresijske analize i neuronskih mreža. Uspoređeni su dobiveni rezultati i neuronska mreža daje bolji opis promatranog fizikalnog sustava. Primjenom simplex algoritma za optimiranje dobivene su optimalne vrijednosti ispitivanih parametara
