This paper presents a methodology to effectively determine the optimal process parameters using finite element analysis (FEA) and design of experiments (DOE) based on Metamodels. The idea is to establish an approximation function relationship between quality objectives and process parameters to alleviate the expensive computational expense in the optimization iterations for the sheet metal forming process. This paper investigated the Kriging metamodel approach. In order to prove accuracy and efficiency of Kriging method, the nonlinear function as test functions is implemented. At the same time, the practical nonlinear engineering problems such as square drawing are also optimized successfully by proposed method. The results prove Kriging model is an effective method for nonlinear engineering problem in practice.