Dynamic Probabilistic Risk Assessment (PRA) is an advanced methodology for risk assessment that uses a computational process to generate a large number of possible scenarios corresponding to the evolution of a system’s state in response to an initiating event. Each scenario consists of a series of possible branches that span the time between the initiating event and either a set ending time or the occurrence of system consequences, such as core damage in a nuclear power plant. Each branch corresponds to the occurrence of a particular stochastic event, and may be a part of multiple different scenarios. The scenarios (consisting of a series of branches) can all be connected in the form of a tree, which functions similarly to a conventional event tree in conventional PRA event tree analysis. The event tree constructed from scenarios generated in dynamic PRA, however, is typically much larger, including scenarios that are difficult to model using conventional PRA methods. These scenarios include physics dependent events, complex dependencies, or variable event times or orders. Part of the value of a conventional event tree is the structure of the tree itself, but since event trees constructed with dynamic PRA methods are significantly larger and more complex, it is challenging to visualize the event tree. This work develops a method to automatically generate graphical event trees from dynamic PRA simulation data. The trees include relevant system dynamics information, as well as depict the scenarios that have been visited and possible branches that were not visited due to the high computational cost of generating scenarios. Visualization of these trees allows for a qualitative analysis of the dynamic PRA analysis that generated the scenarios, and improves the usefulness of dynamic PRA results.