Bicyclists are vulnerable road users and their safety in the road network is a major concern of researchers and authorities. Each year, an average of 35 cyclists are killed and over 2500 cyclists are seriously injured in Australia. In 2008, in Australia, 27 fatalities were cyclists, down from 41 deaths the year prior. Therefore, it is necessary to understand the bicyclists' serious casualty problem in order to reduce the risks of fatality and serious injury in bicycle-involved crashes in the road network. Although a number of studies have investigated the eects of road, environmental, vehicle and human demographic characteristics on bicycle crashes in Victoria, limited research has been conducted to investigate the eects of these parameters on the severity of bicycle crashes. This study compared generalized ordered logit and generalized ordered probit modelling techniques to understand the factors aecting severity of bicycle crashes in Victoria, Australia. It examined the eects of human demographics, road, environmental and crash characteristics on severity of bicycle crashes. Road crash information system (RCIS) database is used to develop the models. The results conrmed that the generalized ordered probit model performed better than the generalized ordered logit model. The results further showed that crash time, bicyclist's age, helmet use, speed zone, lighting condition, bicyclist's intent, other road user's intent, trac control for other road user's approach, spatial location of the crash, road surface of the bicyclist and road layout were the signicant variables aecting the severity of two-vehicle crashes in which at least one bicyclist was involved. This study provided a better understanding of the factors contributing to bicycle serious casualty problem to design and implement safer infrastructure in the road network.