The blanking process used in the manufacturing industry constitutes the first stage of any forming process, which is a widely used process in high volume production of sheet metal components. The main problem faced designers is the selection of an optimum combination of input variables to achieve the desired quality of blanked parts with minimum force. In order to overcome this problem, an effective planning and execution of precisely designed experiments utilizing the power of statistical analysis techniques are used. A Response Surface Method (RSM) was used for the purpose of building a statistical model relating the shearing force (response) to the selected process parameters; tool clearance, height shear angle and punch velocity. The objective of such a model was to enhance the understanding of this relationship and to allow the prediction of the blanking force through the given combination of the input process variables. In addition, the model was used to obtain the optimum combination of the input process variables yielding the minimum blanking force. The results were analyzed using the computer software (MINITABTM, and STATISTICA) and an initial regression model was obtained and refined after performing some appropriate significance tests on the regression coefficients. The refined model was then validated using some regression analysis techniques such as: normal probability plot, lack of fit test and goodness of fit measures. The effects of individual blanking variables and their significant interactions on the response were also investigated. It can be stated that the RSM approach provides a good contribution towards the optimization of sheet metal blanking process.