This study describes application of neural network methods to predict the cutting force model in milling 618 stainless steel. Cutting force was taken as response and the variables (cutting speed, feed rate, axial depth and radial depth). Design of experiments was used to reduce the number of the experiments and provide the optimum experiments condition. The predictive result between experimental result and neural network were compared. The error from the neural network prediction result was acceptable since the value of the prediction was closer to the experimental result.