Traffic congestion is a major problem in Qatar where most of the population are car dependent. The purpose of this study is to understand the influence of various attributes on the system wide and stop level of public buses in Qatar. The study is divided into two parts, macroscopic and mesoscopic levels. In the macroscopic assessment, the study focuses on the bus system in Qatar and the factors affecting ridership, like the population, network expansion, and weather. On the mesoscopic level, the study focuses on factors affecting stop level ridership. A Multiple Linear Regression (MLR) model was developed to identify the parameters that significantly influence the stop level boarding and alighting. The results indicate that planning parameters especially those related to, personal business and shopping places, shopping commuters, restaurant commuters, residents, and number of restaurants are the main factors affecting the bus ridership. This information can help policy makers and public authorities to develop policies and plans to increase the bus usage in the city. The study also investigates the impact of transit accessibility, and population and land use change on ridership. Furthermore, the developed framework can be applied to forecast ridership at potential new stop locations.