<p>Logistics transportation plays a strategic role in the industrial and economic development of countries. In this study, a weighted model of multi-criteria decision-making method adapted to an intuitionistic fuzzy environment is proposed in order to present logistics transportation performance results that can guide decision makers and policy makers. The proposed model is integrated with the Shannon Entropy method, enabling evaluations based on multidimensional data. The research utilizes a panel dataset covering the last ten years for 16 European countries and considers seven performance indicators. In the two-stage analytical process, the first stage involves calculating the weights of the identified criteria. Subsequently, the second stage ranks the countries based on their logistics transportation performance scores. The performance scores are mapped and compared using the Natural Breaks and Excess Risk Map methods. Findings reveal that ‘Cargo and freight transported by air’ was identified as the most influential criterion with an average weight of 0.221, whereas ‘Passengers transported by sea’ had the lowest impact. In terms of country rankings, Germany, France, and Italy consistently demonstrated the highest performance, while Bulgaria and the Baltic states (Lithuania, Latvia) ranked in the lower tier. Furthermore, a significant correlation (0.671) was observed between the proposed model’s rankings and the World Bank’s Logistics Performance Index (LPI), confirming the validity of the results. The results are expected to contribute to analyses conducted under intuitionistic fuzzy environments with multidimensional data and serve as a guiding tool for strategic policy development in the field of logistics. Moreover, due to its original structure, the proposed model is anticipated to offer a significant contribution to the academic literature.</p>