Studies on the impacts of climate change rely on the global projections of the future climate made by General Circulation Models (GCMs). Despite the availability of a growing number of climate model outputs and the continual development of their process representations, considerable uncertainty cannot be eliminated from their future climate projections. This circumstance, combined with other variables, e.g., time and computing limitations, necessitates the selection of appropriate representative GCM-runs (RGCM-runs), reflecting the past and projected future climate, to assess the effects of climate change on different infrastructures. This study is undertaken to select RGCM-runs for Western North America (WNA) based on their ability to simulate past climates between 1981 and 2005 and climatic changes between two 30-year periods, 2071–2100 and 1981–2010, under two representative concentration pathways (RCPs) scenarios, RCP4.5 and RCP8.5. GCMs and their various runs are independently treated as standalone potentials in the selection process, and the initial pool (i.e., full-set) for RCP4.5 and RCP8.5 include 105 and 77 GCM-runs, respectively. We examine GCM-runs reduction by evaluating RGCM-runs performance on three criteria: (i) capturing changes in the climatology of monthly mean precipitation and air temperature, (ii) capturing changes in the monthly mean extreme indices, and (iii) matching the historical and reference datasets (i.e., history matching). For the first two criteria, we employ an envelope-based selection technique, and for the last criterion, gleaning the final RGCM-runs, we present a multi-objective distance-based approach comparing the GCM-runs to reference data sets (i.e., monthly average of temperature and precipitation). This framework selects four RGCM-runs for each RCP to represent the full-set and capture the full range of climatic conditions, including wet-warm, wet-cold, dry-warm, and dry-cold scenarios, which represent the extremes of the climatic spectrum. The results demonstrate that the RGCM-runs can simulate previous climatic conditions and projected changes in key climate variables in WNA, such as temperature and precipitation. This indicates that the selected RGCM-runs are suitable for conducting climate impact assessments and developing adaptation plans for the WNA region.