In real-time systems where tasks have timing requirements, once the workload exceeds the system’s capacity, missed deadlines may incur system overload. Finding optimal scheduling in overloaded real-time systems is critical in both theory and practice. To this end, existing works have encoded scheduling problems as a set of first-order formulas that might be tackled by the Satisfiability Modulo Theory (SMT) solver. In this paper, we move one step forward by formulating the scheduling dilemma in overloaded real-time systems as a Maximum Satisfiability (MaxSAT) problem. In the MaxSAT formulation, scheduling features are encoded as hard constraints and the task deadlines are considered soft ones. An off-the-shelf MaxSAT solver is employed to satisfy as many deadlines as possible, provided that all the hard constraints are met. Our experimental results show that our proposed MaxSAT-based method found optimal scheduling significantly more efficiently than previous works.