This paper addresses the uncertainty associated with release and fire incident rates for trucks in transit carrying dangerous goods. The research extends the treatment of uncertainty beyond sensitivity analysis, low-best-high estimates and confidence intervals, and represents the uncertainty through probability density functions. The analysis uses Monte Carlo simulations to propagate the uncertainty in the input variables through to the resulting release and fire incident rates. The paper illustrates how we can combine information on accident and non-accident releases and fires to generate probability density functions for the total expected releases and fires per billion vehicle kilometres for trucks carrying dangerous goods.