Shot-peening is a mechanical surface treatment used extensively in the industry to enhance the performance of metal parts against fatigue. Therefore, it is important to determine its main parameters and find the optimal values. The purpose of this study is to obtain a statistical model to determine the important parameters of the shot-peening process by considering the effect of sample thickness on the responses and to use this model to obtain multi-objective optimal parameters. For this purpose, response surface methodology was used to determine the governing models between the response variable and the input parameters. Shot velocity, shot diameter, coverage percentage and sample thickness are chosen as shot-peening parameters. Residual compressive stress, its depth and roughness are considered as the response variable. Using finite element analysis, shot-peening process has been simulated. The desirability function approach is used to multi-objective optimization so the optimal shot-peening parameters that simultaneously provide two response variables in optimal mode are obtained. The results shows that surface stress and maximum residual stress are independent of shot velocity, but the depth of the compressible stress and roughness are directly related to shot velocity. In addition, thickness influences on surface stress and the depth of the compressible stress. We can achieve optimal conditions for surface stress, maximum compressive stress, and roughness simultaneously with high-coverage and low-velocity.