For hydrogen fueled vehicles to attain significant market penetration, it is essential that any potential risks be controlled within acceptable levels. To achieve this goal, on-board vehicle hydrogen storage systems should undergo risk analyses during early concept development and design phases. By so doing, the process of eliminating safety-critical failure modes will help guide storage system development and be more efficient to implement than if undertaken after the design-freeze stage. The focus of this paper is the development of quantitative risk analyses of storage systems which use on- board reversible materials, such as conventional AB5 metal hydrides, the complex hydride NaAlH4 or other material candidates currently being researched. Collision of a vehicle having such a hydrogen storage system was selected as a dominant accident initiator and a probabilistic event tree model has been developed for this initiator. The event tree model contains a set of comprehensive, mutually exclusive accident sequences. The event tree represents chronological ordering of key events that are postulated to occur sequentially in time during the accident progression. Each event may represent occurrence of a phenomenon (e.g., hydride chemical reaction and dust cloud explosion) or a hardware failure (e.g., hydride storage vessel rupture). Event tree branch probabilities can be quantified using fault tree models or basic events with probability distributions. A fault tree model for hydride dust cloud explosion is provided as an example. Failure probabilities assigned to the basic events in the fault tree can be estimated from test results, published data, or expert opinion elicitation. To account for variabilities in the probabilities assigned to fault tree basic events and, hence, to propagate uncertainties in event tree sequences, Monte Carlo sampling and Latin Hypercube sampling were employed and the statistics of the results from both techniques were compared.