Partitions in digital PCR (dPCR) assays do not reach the detection threshold at the same time. This heterogeneity in amplification results in intermediate endpoint fluorescence values (i.e., rain) and misclassification of partitions, which has a major impact on the accuracy of nucleic acid quantification. Rain most often results from a reduced amplification efficiency or template inaccessibility; however, exactly how these contribute to rain has not been described. We developed and experimentally validated an analytical model that mechanistically explains the relationship between amplification efficiency, template accessibility, and rain. Using Monte Carlo simulations, we show that a reduced amplification efficiency leads to broader threshold cycle (Ct) distributions that can be fitted using a log-normal probability distribution. From the fit parameters, the amplification efficiency can be calculated. Template inaccessibility, on the other hand, leads to a different rain pattern, in which a distinct exponential tail in the Ct distribution can be observed. Using our model, it is possible to determine if the amplification efficiency, template accessibility, or another source is the main contributor of rain in dPCR assays. We envision that this model will facilitate and speed up dPCR assay optimization and provide an indication for the accuracy of the assay.