Interpreting the functional consequences of genetic variants remains a central challenge in human genomics. Although large-scale sequencing has revealed extensive inter-individual variation, many missense variants are classified as variants of uncertain significance (VUS) due to limited functional evidence. We developed VarMeter, a structure-based and interpretable method for assessing the impact of missense mutations using three-dimensional protein models predicted by AlphaFold. VarMeter evaluates key structural parameters, including normalized solvent-accessible surface area and changes in folding Gibbs free energy (ΔΔG ), enabling quantitative estimation of variant severity without relying on prior variant annotations. By providing physically interpretable metrics, VarMeter complements existing prediction tools and supports both rare disease research and fundamental studies of protein stability and function. This approach contributes to improved variant interpretation and advances precision medicine.