Dominance analysis methods compare pairs of states in a planning task to prove that one is at least as close to the goal as other. Existing methods compute fact-dominance relations, which identify facts that are at least as good as others in any situation. However, this is only possible when a fact is at least as good as another in every single possible context. We introduce a new notion of conditional dominance, which can identify that a fact dominates another under certain conditions. We extend previous methods to compute dominance by taking into account a set of “contexts” in order to find maximal dominance relations. We propose several strategies to find relevant contexts automatically and show that even with one single condition, one can achieve significant pruning in certain domains.