<p>Together with his co-workers, Herbert Simon developed a research program on heuristics in scientific discovery. Simon saw heuristics as both practical tools for problem-solving, as well as descriptive models of how scientists and others solve problems. Building on Simon’s hybrid notion of heuristics as tools and theories, we extend Simon’s study of heuristics in scientific discovery to scientific justification. This article makes two types of contributions, inspirational-practical and conceptual-historical. First, we sketch out how one class of neo-Simonian heuristics, dubbed fast-and-frugal, and originally proposed as descriptive models of how minds make inferences, could enhance the transparency of scientific justification in model selection, and in so doing, the reproducibility of the conclusions drawn from empirical results. Furthermore, we explain how heuristics might serve meta-analyzing findings, aggregating quantitative indicators and qualitative considerations, identifying disconfirming and converging evidence, and examining the robustness of conclusions across different justification tools. Second, we embed our inspirational-practical proposal in a tour d’horizon on the conceptual associates with, and contrasts of, Simonian and neo-Simonian research on heuristics, journeying from early AI to a toolbox view on justification. With those inspirational-practical and conceptual-historical thrusts, we hope to address methodologists interested in ideas for fostering transparency in justification, as well as decision scientists interested in conceptual roots of research on fast-and-frugal heuristics. Finally, we outline what a neo-Simonian research program on heuristics as possible tools for, and descriptive models of, justification might look like.</p>