Climate change, characterized by long-term shifts in temperature and weather patterns, is predominantly driven by human activities. Although numerous factors, such as carbon dioxide concentration, changes in the Earth’s orbit, ocean currents, greenhouse gas emissions, and variations in solar energy reflection or absorption, are recognized as contributors, the degree of their individual impacts remains unclear and uncertain. This study aims to prioritize the contributing factors to climate change by employing the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method integrated with Q-Rung Orthopair Fuzzy Sets (Q-ROFS), a robust approach to handle vagueness and uncertainty in expert assessments. Five domain experts provided linguistic evaluations regarding the importance of each contributing factor. The aggregated linguistic data were analysed using the Q-ROFS-VIKOR model, revealing that two primary factors, identified as R1 and R2, are the most significant contributors to climate change. Interestingly, the factor 'carbon dioxide concentration' was ranked lowest, suggesting a relatively negative impact compared to other factors considered. The findings provide a clearer perspective on the relative significance of various climate change factors, offering valuable insights for policymakers and researchers in designing effective mitigation strategies.