  Process mining is a scientific discipline that analyzes event data, often
collected in databases called event logs. Recently, uncertain event logs have
become of interest, which contain non-deterministic and stochastic event
attributes that may represent many possible real-life scenarios. In this paper,
we present a method to reliably estimate the probability of each of such
scenarios, allowing their analysis. Experiments show that the probabilities
calculated with our method closely match the true chances of occurrence of
specific outcomes, enabling more trustworthy analyses on uncertain data.
