The shearing processes such as the blanking and piercing of sheet metals have been often used to prepare workpiece for subsequent forming operation. The sheared plane plays an important role in the shearing products’ dimension precision and their functions. The quality of sheared plane is affected not only by the material characteristics but also by the process parameters. In the current study, the finite element method is used to investigate the shearing process of sheet metals. Then, the neural network was employed to construct the relationship model of shearing process parameters related to the fracture depth of sheared plane, such as blank holding force, die corner radius, punch-die clearance, friction factor and punch speed,. The result and approach obtained from this study would be beneficial to stamping industries because they provide the reference for the prediction of shearing process.