CONTEXT Mediterranean peri-urban regions have changed considerably in recent decades, leading to different farming system trajectories. The high level of heterogeneity and complexity of these areas are particularly challenging in terms of understanding the ongoing processes and their drivers, including the effects of spatial interactions, in order to make an initial assessment of the possible levers for territorial management. OBJECTIVE We aim to show a new modeling approach to assess the factors explaining farming system trajectories on Mediterranean peri-urban areas, including an analysis of the spillover from neighboring areas, which is often neglected in these kinds of methods. The model was tested in two urban regions, located in Pisa (Italy) and Avignon (France), leading to very different perspectives, given the differences in terms of farming systems and environmental characteristics. Our model also highlights the factors acting on peri-urban farming system trajectories. METHODS We first analyzed the farming systems characteristics and their trajectories, based on a land parcel identification system database and agricultural census. Then, we estimated explanatory factors at the farm level applying a spatially explicit model which takes into spatial autocorrelations into account: a Spatial Autoregressive Probit model. RESULTS AND CONCLUSIONS Our results provide new evidence supporting the hypothesis that peri-urban farming systems trajectories are influenced by other variables than the distance to the city center and the urbanization processes. Although urban sprawl characterizes medium-sized regions, this factor is not relevant on farming systems trajectories in the region of Pisa, where structural agro-pedoclimatic drivers contribute more significantly to the probability of change and, therefore, highlighting the greater stability of these farming systems. The region of Avignon reveals different aspects: a dense road infrastructure and favorable environmental conditions (availability of irrigation water during warm periods, adequate temperatures in winter, deep soils) increase the probability of intensification within the farming system. SIGNIFICANCE Our methodological approach, which is based on a spatial probit model, measures the effect of the spatial dependence of the dependent variables. In addition, the preliminary classification in terms of farming systems improves our understanding of the land trajectories. The results obtained provide new insights into the processes underway in Mediterranean peri-urban areas.