<p>This research offers a novel approach to enhance the fuzzy systems decision-making process, specifically for the complicated transportation-related scenarios. All other transportation-related domains, including those where conventional multi-criteria decision-making (MCDM) techniques are effective, are inherently unpredictable. The following approach addresses the problems caused by this inherent uncertainty: the Multi-Distributive Weighted Function, which uses distributions such as the t-distribution, gamma distribution, and Poisson distribution to refine decision-makers’ weightings; and the Pythagorean fuzzy entropy method, which ensures accurate weight calculations for criteria. The integration of several methodologies results in a holistic solution to intricate transportation challenges, hence enhancing the dependability and efficiency of decision-making. The Pythagorean fuzzy entropy approach improves attribute selection and ranking accuracy, while the Multi-Distributive Weighted Function (MCDW) guarantees the production of resilient conclusions in the face of decision-makers’ uncertainties. The combined methodology considerably enhances the processes of decision-making in fuzzy systems, especially when uncertainties result in inaccurate conclusions. In order to verify decision-making’s accuracy and efficiency, a sensitivity analysis is used to examine the model’s performance.</p>