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Real-world problems are subject to various uncertainties. To cope with diculties arising in those situations, there has been increasing attention to optimization problems under uncer-tainty in recent years. However, just a few works have dealt with Mathematical Programs with Equilibrium Constraints (MPEC) under uncertainty. In particular, there have been very few studies on a robust optimization approach to those problems. In this paper, we formulate an MPEC under uncertainty as a Mathematical Program with Second-Order Cone Complementarity Constraints (MPSOCCC). Since the MPSOCCC is di-cult to deal with directly, we use a smoothing function to approximate the problem and solve a sequence of smooth approximation problems to get a solution of the original MPSOCCC. The main theoretical result of this work is to establish that the proposed smoothing method has the global convergence property to a stationary point of the MPSOCCC. Content