Model validation experiment is a new type of experiments, of which the goal is to determine the credibility of the simulation model. In order to obtain low cost and high credibility of a model validation experiment, a methodology of model validation experiment design considering random uncertainty is presented. Firstly, by extending the concept of area metrics, a dimensionless model validation metric (area metric factor) is proposed, and a criterion for qualitative assessment of accuracy of simulation models based on expert systems is developed. Then, an optimization model for model validation experiment design considering random uncertainty is constructed. Meanwhile, an optimization method is developed to solve the optimization model. Finally, two simulation examples are used to illustrate the proposed methods. The simulation results show that the randomness of experiment design affects the reliability of the model evaluation results in the case of small samples. The area metric factor converges with the increase of the number of experimental observations. The proposed method for model validation experiment design can avoid the effect of testing program on the result of model validation.