We present BLIMMP-Explorer, an interactive visualization system for BLIMMP, a Bayesian tool we developed for inferring metabolic module presence from prokaryotic genomes. Probabilistic tools for metabolic module inference produce layered evidence that tabular outputs cannot clearly communicate. BLIMMP-Explorer renders each module as a gene-centric directed acyclic graph with split-circle nodes encoding two independent evidence values, step-level probability annotations, and flag-based indicators of annotation quality. An influence panel decomposes the probability shift contributed by associated enzymes across a global co-occurrence network. We demonstrate the system on Pseudomonas fluorescens SBW25 through two use cases: (i) recovering a pathway in an incomplete genome and (ii) identifying a false positive by reviewing annotation flags and competing enzyme annotations. The visualization enables reasoning that would otherwise require manual cross-referencing of multiple output files.