The objective of this study was to develop models for forecasting ridership at an individual transit stop or route section. This study addressed fixed-route transit services provided by the Adelaide Metro in the Western Statistical Sub-division and estimated boardings in one direction (towards the city) during morning peak and inter-peak periods. It used accurate methods to allocate demographic and socio-economic data from census areas to service areas. Ordinary Least Square regression (OLS) and Geographically Weighted regression (GWR) models were used to develop the relationships between transit ridership and socio-economic variables, land use and levels of service. The models gave logical results for the bus and rail service areas with significant predictive accuracies. The most significant variables that influenced transit ridership included headway (waiting time), distance to the city, population density, percentage of students and median household income within the transit service area. Refereed/Peer-reviewed