Alternating Direction Method of Multipliers (ADMM) is an effective method for solving separable convex optimization problems. In this paper, the method is extended to solve Sylvester equations with nonnegative constraint. We give a convergence result showing that the algorithm converges to a Karush-Kuhn-Tucker point whenever it converges. Numerical evidence shows that the proposed algorithm can efficiently solve nonnegative Sylvester equations.