Risk analyses always involve uncertainty which depends on the knowledge analysts have of the phenomenon they are dealing with. So, in order to use risk analyses results in a more transparent, aware and justified way, it is important to characterize and quantify this uncertainty. Unfortunately, in the field of natural risks, present analyses are mainly deterministic and do not allow uncertainty representation. The aim of this study is then proposing and testing Monte Carlo methods, which have already been adopted in other research fields, as tool for probabilistic risk analyses. In particular, the suggested method develops the seismic «Renewal Process» in a new methodology which allows to quantify and characterize both input and output parameters uncertainty. A case study, regarding the Garfagnana region, has validated the methodology. The added value of the proposed method is its transferability in the analyses of other natural hazards
This paper is available in Italian only.