In this paper we propose a method for designing optimum degradation test based on nonlinear random-coefficients models. We use the approximated expression of the Fisher information matrix for nonlinear random-coefficients models. We apply the simplex algorithm to the inverse of the determinant of Fisher information matrix to satisfy the D-optimal criterion. By comparison of the results from PDP degradation data, we suggest a general guideline to obtain optimum experimental design for determining inspection intervals and number of samples in degradation testing.