Road traffic accidents are a major global socio-economic problem, affecting all people of the world and Ethiopia is a country with a very large number of traffic accidents and fatality rate. This study has major objective of assessing the predictors of road traffic accident in Bahir Dar city, Ethiopia and identifies factors that contribute to the occurrence of road traffic accidents that leads human death. Data regarding to the number of deaths per road traffic accident were obtained from Bahir Dar city administration traffic police office for a two year period from July 2015-June 2017. In this study applies six count models namely Poisson, negative binomial (NB), generalized Poisson (GP), zero inflated Poisson (ZIP), zero-inflated negative binomial (ZINB) and zero inflated generalized Poisson (ZIGP) regression models. Based on different model comparison, (using AIC, log likelihood and Vuong test) ZIGP regression model provides more appropriate fit to the road traffic accident (the number of human death per road traffic accidents) data considered in this study. Sex of driver, age of driver, driving under alcohol, driving under fatigue, not give priority, days of weeks, road condition, overloading, over speeding, and type of accident were found to be statistically significant predictors of human death due to road traffic accident. Keywords: RTA; over dispersion; AIC; BIC; count data; Ethiopia