Morphometric watershed prioritization has been widely utilized in mountainous areas to identify critical regions for soil loss, sediment yield, and flooding. However, all previous studies started with ranking the computed parameters and ended with the ranking of compound values, losing the quantitative distance between measurements in the ranking process, and results with a range of incomparable compound values among studies. This study proposed a methodological improvement framework integrating a geographical information system and multivariate statistics to calculate the Watershed Morphometric Composite Index (WMCI). The study has introduced a feature scaling approach to the morphometric measurement based on the relationship of parameters with soil erodibility and constructed a composite index of parameters. The framework is successfully applied to prioritize sub-watersheds in the southern slope of the central Himalayas and validated with RUSLE-based soil loss, RUSLE-SDR-based sediment yield, and field observation. The framework is simple but robust in assigning the weight to the parameter, and the composite index values range from 0 to 1 regardless of the number of sub-watersheds, properties, or parameters chosen. The study concluded that the soil erodibility feature scaled composite index provides good agreement with potential soil erosion compared to previous morphometric prioritization methods and can perform better than the factor analysis-based technique if the parameters are selected carefully. The proposed WMCI has demonstrated its ability to mainstream the sub-watershed prioritization process precisely and will be useful in making clear decisions compared to traditional methods for effective watershed conservation, ultimately aiding development planning, prudent resource allocation, and ecological restoration.