The technology of accelerated testing with competing failure is the foundation of application extending from products with simple structure to products with complex structure. Designing optimal test plans, which obtains better result with lower cost, is one of the main research points in the technology. Traditional analytical optimization has some shortcomings, such as complexity of deduce process. To overcome these shortcomings, this study presents a new method of Monte Carlo simulation based optimal designs for accelerated testing with competing failure. When the candidate plans are too many, curve fitting can be introduced to decrease the amount of calculation by reducing the number of test plans for simulation. Two cases of simulation based optimal designs are demonstrated by direct and indirect optimization respectively, which shows that the proposed method is suitable for application. Results of sensitivity analysis show that this method is robust.