Wetness of the host surface is a critical environmental factor for the development of foliar fungal diseases, but it is difficult to estimate the wetness durations required by pathogens for infection when only few experimental data are available. In this paper, we propose a method to estimate wetness duration requirements of foliar fungal pathogens when precise experimental data are not available. The proposed method is based on approximate Bayesian computation. It only requires lower and upper bounds of wetness duration requirements for one or fewer temperatures. We describe the method, show how to apply it to an infection model, and then present a case study on Mycosphaerella nawae, the causal agent of circular leaf spot of persimmon. In this example, the parameters of a simple infection model were estimated using experimental data found in the literature for the pathogen, and the model was applied to assess the risk in a Spanish area recently affected by the disease. The results showed that the probability of successful infection was higher than 0.5 for 32% of the on-site wetness durations recorded in the affected area. Results obtained with simulated data showed that our method was able to improve the estimation of wetness duration requirement. Given the flexibility of the proposed method, we expect it to become adopted for assessing the risk of introduction of exotic fungal plant pathogens.