I study an optimal design of monetary incentives in experiments where incentives are a treatment variable. I introduce the Budget Minimization problem in which a researcher chooses the level of incentives that allows her to detect a predicted treatment effect while minimizing her expected budget. The Budget Minimization problem builds upon the power analysis and structural modeling. It extends the standard optimal design approach by explicitly making the budget a part of the objective function. I show theoretically that the problem has an interior solution under fairly mild conditions. I illustrate the applications of the Budget Minimization problem using existing experiments and offer a practical guide for implementing it. My approach adds to the experimental economists' toolkit for an optimal design, however, it also challenges some conventional design recommendations.