Consider the context of the Multi-Objective Ranking and Selection (MORS) problem, which is a multi-objective simulation optimization problem on a finite feasible set of systems. Since the Pareto set can only be observed with error, MORS methods often are concerned with the possibility that a misclassification (MC) event occurs, in which a system is misclassified on its status as Pareto or non-Pareto. In two dimensions, phantom Pareto systems have been used to assist in analyzing the probability of an MC event. We construct phantom Pareto systems in d dimensions, describe an algorithm to efficiently locate the phantom Pareto systems in d dimensions, and describe how the phantom Pareto systems can be used in a SCORE framework.