Abstract Inductive definitions and justifications are wellstudied concepts. Solvers that support inductive definitions have been developed, but several of their computationally nice properties have never been exploited to improve these solvers. In this paper, we present a new notion called relevance. We determine a class of literals that are relevant for a given definition and partial interpretation, and show that choices on irrelevant atoms can never benefit the search for a model. We propose an early stopping criterion and a modification of existing heuristics that exploit relevance. We present a first implementation in MinisatID and experimentally evaluate our approach, and study how often existing solvers make choices on irrelevant atoms.