In the contemporary era of technological advancement, smartphones have become an indispensable part of individuals’ daily lives, exerting a pervasive influence. This paper presents an innovative approach to passenger counting on buses through the analysis of Wi-Fi signals emanating from passengers’ mobile devices. The study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels, thereby addressing a crucial aspect of public transportation. The proposed system comprises three crucial elements: Signal capture, data filtration, and the calculation and estimation of passenger numbers. The pivotal findings reveal that the system demonstrates commendable accuracy in estimating passenger counts under moderate-crowding conditions, with an average deviation of 20% from the ground truth and an accuracy rate ranging from 90% to 100%. This underscores its efficacy in scenarios characterized by moderate levels of crowding. However, in densely crowded conditions, the system exhibits a tendency to overestimate passenger numbers, occasionally doubling the actual count. While acknowledging the need for further research to enhance accuracy in crowded conditions, this study presents a pioneering avenue to address a significant concern in public transportation. The implications of the findings are poised to contribute substantially to the enhancement of bus operations and service quality.