<p>Selecting appropriate solar panels for photovoltaic systems is a multi-criteria decision-making problem involving technical, environmental, and customer-oriented trade-offs. Existing studies typically rely on a single weighting or ranking technique, which can obscure how methodological choices influence final decisions and limit the robustness of results. To address this gap, this study proposes a hybrid subjective–objective multi-criteria decision-making framework that explicitly compares alternative weighting and ranking paradigms rather than relying on a single integrated pipeline. Criteria weights are derived using both the Best–Worst Method, which captures expert preferences, and the Criteria Importance Through Inter-criteria Correlation method, which reflects data-driven variability and inter-criteria correlations. Solar panel alternatives are then evaluated using two complementary ranking approaches, Technique for Order Preference by Similarity to Ideal Solution and Measurement of Alternatives and Ranking according to the Compromise Solution, which enable a structured comparison of distance- and compromise-based decision logics. A case study of five commercially available solar panels, evaluated across fifteen criteria, demonstrates that panel rankings are highly sensitive to the choice of weighting and ranking methods. Results reveal that technically superior panels dominate under subjective weighting, while alternatives with balanced environmental and customer attributes gain prominence under objective weighting. The comparative analysis highlights how different decision-making paradigms yield divergent yet explainable outcomes, providing transparent decision guidance rather than a single prescriptive ranking. The proposed framework enhances robustness, interpretability, and strategic alignment in solar panel selection, providing a flexible decision-support tool for researchers, practitioners, and policymakers in PV system planning.</p>