This paper investigates the factors influencing accident likelihood of motorcyclists in Taiwan by using the data collected by Institute of Transportation, MOTC in 2001. Different models, including Poisson, Negative Binomial, Zero-Inflated Poisson and Hurdle, are applied to model count date, as the dependent variable. Zero-inflated and Hurdle models with two parts have a more general dual regime data generating process in overcoming the problem when the number of zeros in the data exceed what would typically be predicted, compared to Poisson and NB models. The results indicate that the effects of dangerous driving behavior on the accident likelihood appear to be significant in "driving frequency over six days per weed and vehicle age over seven years". The factors that significantly influence the accident likelihood of motorcyclists are "personal monthly income", "age", and "cumulative mileage".