This paper introduces a novel approach to large-scale group decision-making, addressing the challenge of effectively aggregating diverse expert opinions. By integrating the Ranking Comparison (RANCOM) method into the aggregation process, the approach minimizes the impact of individual inaccuracies on the final results. The study compares six aggregation techniques through simulation experiments and a practical case study on solar panel evaluation. Additionally, it proposes a new fuzzy ranking-based method for aggregating group results. The research highlights the importance of accounting for inaccuracies in individual assessments and subtle differences in expert opinions. Key contributions include an improved method for aggregating expert input and a robust framework for large-scale group decision-making, enhancing the reliability of outcomes in complex multi-criteria scenarios.