The year 2022 in Italy registered an increase of 170% in forested and non-forested areas devastated by fire (in 2021, fires affected 159,437 hectares). In detail, the highest number of calls to the fire fighters was recorded in Sicily and Calabria, with 301 and 223 requests respectively. The Calabria Region, with 35,480 hectares of forest area destroyed in the year 2021, is a strategic study area for conducting an in-depth analysis of how fires are spread and distributed. In light of this, the present work proposes to estimate the fire risk in the region using a non-parametric statistical technique called Smooth Kernel Distribution (SKD). This technique allows us to estimate the probability density function of a continuous random variable based on a sample dataset of the temporal sequence and geospatial location of fires in the region over the last decade. The main potential of the adopted method is that the SKD allows the creation of risk maps based on historical data, identifying high-risk areas and ensuring the development of targeted preventive actions. The preliminary results obtained in the study area show that the SKD is a powerful tool for analysing fire risk. The identified risk maps show the areas in the region with the highest fire risk, enabling the competent authorities to take preventive measures to avoid further damage. Furthermore, the research conducted has shown that the use of the SKD in combination with other statistical techniques, such as multivariate analysis, can provide a more comprehensive understanding of fire risk in the region (intensity of the fire, vegetation maps, terrain orography).