Abstract : Agricultural intensification has greatly decreased grassland surface area in some regions, thus changing grassland management and modifying environmental and socio-economic systems. Therefore, knowledge about grassland management practices in farming systems is needed for sustainable agriculture. In this context, the PaturMata model simulates grassland management at the farm scale. The PaturMata model simulates grassland dynamics and several factors such as farming practices, grass consumption, and fertilization. The model takes into account environmental and farming system parameters such as climate, field number, size, and location; livestock units; and conventional or organic agriculture. Here, we first ran the model under climatic conditions favorable to grass growth for four farms on an experimental site located in western France. Biophysical variables extracted from remote-sensing images were used to initialize PaturMata, whose predictions were compared to on-site surveys. We generated forecasting scenarios of the same farms under different climatic conditions. Results show that PaturMata predicts a 70 % decrease in grass consumption, a 50 % decrease in the number of annual grazing periods, and a 60 % increase in the amount of conserved forage consumed, when conditions are unfavorable to grass growth. We conclude that the PaturMata model can help design farms and management strategies capable of coping with a wide range of conditions.