Probabilistic approaches are widely adopted for the modeling of rockfall trajectories, but are not widely discussed in the literature. This paper aims to help fill this gap by reviewing probabilistic models of rockfall trajectories, while providing some perspectives for future study. We first make it clear that, from a theoretical point of view, the probabilistic approach is necessitated by both the ontic (inherent) uncertainty associated with rockfalls and the epistemic (information) uncertainty associated with numerical modeling. The review suggests that there may be the potential to improve the probabilistic modeling of rockfall trajectories in various aspects, including the systematic probabilistic modeling criterion, the random sampling approaches employed for probabilistic variables, the probabilistic modeling of rock shape, and the probabilistic prediction of rockfall intensity. However, there are still some open questions regarding the promotion of probabilistic modeling in practice. It is not clear whether probabilistically treating all of the variables of rockfall trajectory model with reasoned distributions will lead to significantly improved results, or whether the improvements will be great enough (given the difficulties and costs involved) that it is worth quantifying all of the uncertainties involved in rockfall trajectory modeling. The answers to these questions can be found in the practice of probabilistic modeling itself.