Pest risk assessment studies are aimed at evaluating if weather conditions are suitable for the potential entry and establishment of an organism in a new environment. For fungal plant pathogens, the crucial aspect to be explored is the fulfillment of the infection process, that constitutes the first phase of the development of an epidemic as mainly driven by temperature and leaf wetness duration. This is of par-ticular interest for climate change studies, because the modified pattern of temperature and moisture regimes could completely alter the known distribution and severity of plant disease epidemics. Biophys-ical process-based models could effectively be used in such studies, because they allow, within their applicability range, estimating organisms responses to climatic drivers in environmental conditions not yet experienced. One of the prerequisite of their adoption in operational contexts is a sensitivity analysis assessment aimed at understanding their ability (i) to differentiate the responses according to different parameterizations and (ii) to be sensitive to the variability of the input data. In this study, a generic potential fungal infection model simulating four pathogens chosen to provide a wide range in temper-ature and moisture requirements was analyzed. The model was run under diverse climatic conditions. The sensitivity of the model significantly changed according to the pathogen tested, and the relevance of its parameters in explaining model output resulted strongly linked to the environmental conditions tested, indicating its to be used in pest risk assessment studies.