A general procedure to evaluate future trends in snow loads on structures is illustrated aiming to study influences of climate change at European scale, to assess its impact on the design of new structures as well as on the reliability levels of existing ones, also in view of definition of updated snow maps for new generation of Eurocodes. Starting from reliable and high quality registered meteorological data of daily temperatures, rain and snow precipitations at nine Italian weather stations, conditional probability functions of occurrence of snow precipitation, accumulation and melting have been preliminarily determined as functions of daily maximum and minimum air temperatures. Based on the above mentioned conditional probability functions, an innovative numerical procedure has been setup, that, starting from daily outputs of climate models in terms of maximum and minimum temperatures and water precipitation, allows, by means of Monte Carlo simulations, to determine the yearly maxima of snow loads for a convenient time interval, 40 years, and then, via the extreme value theory, the characteristic ground snow load. The proposed procedure has been preliminarily validated reproducing data series measured in the above mentioned weather stations in the period 1950–1990 and, subsequently, it has been applied to simulate the evolution of characteristic ground snow loads at these sites in the period 1981–2100. In the analysis, which considered 40 year time windows shifted ten years each time, they have been taken into account not only the forecast data derived by different climate models, but also the reference data, in the period 1981–2005, pertaining to the so-called historical experiments. Finally, the proposed procedure has been implemented in a more general methodology for snow map updating, in such a way that the influence of gridded data, predicted by global climate models, on extreme values of snow loads is duly assessed. Preliminary results demonstrate that the outlined procedure is very promising and allows to estimate the evolution of characteristic ground snow loads and to define updated ground snow load maps for different climate models and scenarios