Traffic management at the entrance points of passenger terminals is recognized as a critical challenge in transportation systems. While precise scheduling and traffic control are feasible under deterministic departure and arrival times, real-world terminal operations are characterized by significant temporal uncertainty. This uncertainty arises from a combination of human, technical, managerial, and environmental factors affecting bus movements. In this study, a fuzzy-based modeling framework is proposed to analyze traffic conditions at terminal entry points by explicitly accounting for uncertainty in bus departure and arrival times. To identify the most influential factors, a structured questionnaire was developed, including 13 parameters classified into four main categories: driver and passenger psychological factors, vehicle-related factors, terminal management factors, and environmental traffic conditions. Expert opinions were collected from transportation specialists, and both classical and fuzzy weighting approaches were applied to evaluate the direct effects of individual parameters as well as their interactions. A Gaussian probability density function was employed as the fuzzy membership function to represent the continuous and uncertain nature of traffic-related variables. The results indicate that driver experience, potential vehicle breakdowns, management of terminal entry points, and surrounding traffic conditions play the most significant roles in influencing congestion at terminal entrances. The proposed fuzzy framework is designed as a decision-support tool for terminal management under uncertainty and is particularly suitable for situations where reliable real-time traffic data are unavailable