The increasing interest in agro-environmental management entails having tools to assess, monitor and map agro-environmental functions (AEFs) in different regional contexts. In Europe, decision-making in agro-environmental policies generally targets single functions instead of multiple ones and rarely considers the regional variability of agri-cultural or geo-physical conditions that may influence the fulfillment of functions. We propose and test a method to assess the potential of farming regions to fulfill a set of AEFs. The method was applied in the ''Collina interna grossetana'' farming region (Italy) and concerned three functions: protection of surface water from nitrates, protection of soil from erosion, and conservation of landscape diversity. These functions were qualified and mapped using various geo- physical and land cover descriptors from common geographical datasets. All of the descriptors were combined using geographical cluster analysis to identify their contribution to the three functions, and thus to assess the potential of the farming region to fulfill these functions. Three levels of potential were calculated, according to the more or less favorable fulfillment of soil and water functions. No totally favorable contribution to the functions was identified in the studied area. Moreover, we mapped the spatial patterns obtained for the different levels of potential. The landscape diversity function was found to be the least variable in the study area, while different patterns were identified for the other functions. In fact, the northern and central sections of the study region were organized more in the form of large core areas of different levels of potential, whereas the southern section presented more boundary areas, small core areas and isolated pixels. The method may help to establish local priorities in agro-environmental management pointing out where the set of functions is completely or partially fulfilled, as well as where and how it is more or less necessary to focus support measures afforded by environmental policies. Such information could help to palliate the current poor consideration of the spatial variability of functions in regional policies.