We present a structured multi-criteria framework for the sub-selection of CMIP6 global climate models (GCMs) to support CORDEX-CORE2 dynamical downscaling. The framework integrates five key criteria: historical performance, model independence, regional temperature sensitivity, precipitation spread, and data availability, and is designed to identify a single, consistent subset of GCMs across all CORDEX domains to improve the comparability and interpretability of regional projections. A total of 45 GCMs are evaluated over the historical period (1981–2014), with 31 models further assessed for projected changes over 2015–2100. Application of the framework shows that model performance is systematically higher for large-scale circulation and thermodynamic fields than for precipitation seasonality and monsoon-related processes, which remain a dominant source of uncertainty across regions. Despite the diversity of climates represented across CORDEX domains, model rankings are broadly consistent, with top-performing models exhibiting stable performance across both tropical and extratropical regions, while lower-ranked models show more pervasive deficiencies rather than region-specific weaknesses. Sensitivity analyses demonstrate that rankings are largely insensitive to the choice of aggregation method but depend strongly on the breadth of evaluation metrics, with robust and reproducible rankings emerging only when a large fraction of the full metric suite is retained. Assessment of model independence reveals substantial clustering within the ensemble, indicating that many models share similar performance characteristics, while a smaller subset provides distinct and complementary information. Regional temperature sensitivity exhibits a coherent ordering across domains, suggesting that differences in projected warming are primarily governed by intrinsic model characteristics rather than region-specific effects. In contrast, precipitation spread shows strong regional variability, with both the magnitude and temporal structure of precipitation change differing widely across models. The relationship between precipitation and warming further highlights that, in some regions, precipitation responses scale with temperature, while in others they are dominated by circulation variability. By combining these criteria with data availability constraints, the framework identifies a reduced set of models that retains key aspects of performance, diversity, and projected change. This approach provides a transparent and reproducible basis for GCM selection within CORDEX-CORE2 and offers a generalizable strategy for coordinated regional climate modeling efforts.