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Cattle ranchers have problems making informed decisions for the management of natural pastures. The lack of information ends up forcing the animals to be supplemented with external feed and forage. The degradation of natural pastures, climate change, and agricultural policies aimed to make farms more sustainable. Sustainability requires improving natural resource management techniques. Voisin Rational Grazing manages grazing time based on the critical leaf area index; it has been proposed as a sustainable alternative for livestock. This method is based on optimizing the productivity of pasture and livestock but requires constant plots monitoring. The objective was to estimate through remote sensing the evolution of growth, biomass, and other pasture management parameters, which facilitate decision making in the Voisin. A real case study was chosen. The farm has 240 ha in 81 paddies in 5 counties, and 1,703 ha of communal pastures in joint use for summer use. It is in the northern of Madrid, in Central Spain under Mediterranean climate. Sentinel-2 images were used between 2017 and 2020, the processing and calculation of the vegetation indices was carried out with Sen2Cor and QGIS. In the field, biomass was sampled, and images were taken and processed with QGIS and SW Maps. A wide variety of factors affect the farmer decision, making the dynamics of the pastures between the plots heterogeneous in phenology and production. The evolution of the vegetation indices follows the dynamics of the grass logistic curve. Vegetation indices seem appropriate to detect the point of maximum grass biomass gain, necessary to apply the Voisin. Plots that are being grazed at high instantaneous stocking density, characteristic of the Voisin, can be detected using vegetation indices. Also, it was appreciated how this grazing method allows rapid regrowth. We considered that remote sensing can facilitate the application of Voisin Rational Grazing.