Polytopic Fuzzy Set (POFS) is a mathematical framework for quantifying uncertainty, ensuring that the total of the \({q}^{th}\) power of positive, neutral, and negative membership grades does not exceed a maximum threshold of one. POFSs offer a broader overview of uncertain information, enhancing their effectiveness compared to Picture Fuzzy Sets (PFSs) and Spherical Fuzzy Sets (SFSs). The drawbacks of the current Score and Accuracy functions for Polytopic Fuzzy Numbers (POFNs) are established in this work. Better Score and Accuracy functions are introduced for more trustworthy comparisons to overcome these issues, and the paper also proposes a novel Confidence Level Polytopic Fuzzy Weighted Geometric (CPOFWG) aggregation operator (AO). Moreover, incorporating POFSs alongside decision-makers (DMs) confidence levels regarding a decision-making problem. Finally, a novel Multi-Criteria Group Decision-Making (MCGDM) approach is introduced, incorporating the proposed score, accuracy function, and aggregation operator. This approach is utilized to address the Green Supplier Selection (GSS). Its effectiveness is evaluated by comparing it with other established methods. Furthermore, a sensitivity analysis is conducted to ensure the robustness and credibility of the result.