Wet snow conditions trigger the formation of ice sleeves on overhead power lines and increase the likelihood of heavy snowfall, which can cause severe infrastructural damage and, consequently, prolonged interruptions to the National Transmission Network. To develop action plans aimed at enhancing the resilience of the power grid, probability maps of expected events are needed. These maps have been developed by processing the results of 11 high-resolution Euro-CORDEX models (spatial resolution ~12 km), assuming a Business-As-Usual scenario (RCP8.5). The MERIDA meteorological reanalysis dataset (spatial resolution 7 km), covering the period 1986-2019, was used to “bias-correct” the models using the “Equidistant Quantile Mapping” technique. MERIDA was also used to implement a modified formulation of the Makkonen model to describe the growth of ice sleeves on high-voltage overhead lines using daily weather data, and to develop a simple snow model to estimate the snow load on the ground. After validating the two codes by comparing the results with some observations, they were applied to the climate models to assess these phenomena up to 2060 and derive future scenarios. The probability maps were created using the Generalized Extreme Values statistical technique, which describes the expected values at different time horizons: 2020, 2030, 2040, and 2050. The results indicate that these phenomena will generally decrease as snowfall shifts to rain due to global warming. However, these same events might intensify in higher regions in the Alps, as in a warmer climate, temperatures between -1.5 and +2 °C will become more likely, allowing wet snow events to occur at altitudes previously spared due to their typically cold temperatures.