Generic models can be relevant tools for exploring and comparing the impact of climate change on the development of crop diseases. The infection process of foliar pathogens is mainly driven by surface wetness duration (SWD) and temperature. Hence, our objective was to propose a generic response function that attempts to be robust (adapted to the infection process of many foliar pathogens), and easy to apply (well-informed parameters in the literature). This model was then used to quantify the impact of climate change on four foliar fungal pathogens, in the French context. First, the infection was modeled as a function of, both, temperature and SWD, using a simplified version of the sigmoidal Weibull equation. The upper asymptote of this equation was described by linear functions between four cardinal temperatures. Second, this model was fitted and validated with published data from 19 controlled laboratory studies. Especially low relative root mean square errors (RRMSE) were obtained for species in the genera Colletotrichum (about 0.11) and Puccinia (about 0.23). Last, the model was used to assess the CC impact on the infection rate and frequency of Albugo occidentalis, Phytophthora ramorum, Cercospora carotae and Botrytis cinerea. The simulations showed different trends, according to the four pathogens and climate sites: an increased frequency of infection and of the rate of infection of A. occidentalis and P. ramorum, in northern France, and the maintaining or the decrease of the frequency and rate of infection, at more or less long-term, for C. carotae and B. cinerea, in southern France. The importance of microclimate in the canopy, to explain the infection process, could justify coupling this generic model of infection to a mechanistic model based on energy balances, to simulate temperature and SWD, within the crop cover, rather than at the weather station scale.