In order to produce shell parts with different applications, using the new method in sheet metal forming is inevitable. The last decade has shown an increasing interest in a new on the sheet A Computer Numerical Control (CNC) milling machine can be used to create the special tool path. In this method because of clamping the sheet edge during the process, there is no material flow to the forming area. As a consequence, the part thickness strongly decreases. In this research, based on a Toguchi Design of Experiment, 25 experiments have been done and effect of four process parameters included tool diameter, axial pitch, feed rate and rotational speed on thickness variation of produced parts are studied experimentally. Actually, the TDoE is an important branch of experimental design, particularly when several input variables potentially influence some performance measure or quality characteristic of the product or process, allowing a reduction of the experiments number. Also an artificial neural network model is developed to predict the thickness variation of the produced parts. An NN can be considered as a black box since a designer can use it in a very simple way without the complete knowledge of the existing relationships between input and output. Keywords: Incremental Forming, Taguchi Design of Experiment, Thickness Variation, Artificial Neural Network. .