SNPDogg is a machine-learning classifier designed to predict the harmfulness of genomic mutations in humans. This tool addresses the challenge of assessing the potential damaging effects of the roughly 3 million mutations present in the human genome, many of which remain uncharacterized. SNPDogg provides users with transparent insights into its prediction process through interpretable graphical displays of feature contributions. Additionally, SNPDogg boasts accuracy comparable to other state-of-the-art tools while offering unique transparency features. It is positioned as a valuable resource for clinicians and researchers involved in variant assessment, offering a user-friendly interface and interpretability that simplifies the evaluation process. Further development of SNPDogg includes plans to expand its capabilities to include scoring for INDELs (insertions/deletions) and native compatibility with the GRCh38 genome build, enhancing its utility and coverage of genetic variants.