Statistical distributions of annual extreme (AE) and partial duration (PD) for rainfall events are analysed using a database of 50 rain-gauge stations in Peninsular Malaysia, involving records of time series data which extend from 1975 to 2004. The generalised extreme value (GEV) and generalised Pareto (GP) distributions are considered to model the series of annual extreme and partial duration. In both cases, the three parameter models such as GEV and GP distributions are fitted by means of L-moments method, which is one of the commonly used methods for robust estimation. The goodness-of-fit of the theoretical distribution to the data is then evaluated by means of L-moment ratio diagram and several goodness-of-fit (GOF) tests for each of the 50 stations. It is found that for the majority of stations, the AE and PD series are well fitted by the GEV and GP models, respectively. Based on the models that have been identified, we can reasonably predict the risks associated with extreme rainfall for various return periods.