Brachiaria grasses are sown in tropical regions around the world, especially in the Neotropics, to improve livestock production. Waterlogging is a major constraint to the productivity and persistence of Brachiaria grasses during the rainy season. While some Brachiaria cultivars are moderately tolerant to seasonal waterlogging, none of the commercial cultivars combines superior yield potential and nutritional quality with a high level of waterlogging tolerance. The Brachiaria breeding program at the International Center for Tropical Agriculture, has been using recurrent selection for the past two decades to combine forage yield with resistance to biotic and abiotic stress factors. The main objective of this study was to test the suitability of normalized difference vegetation index (NDVI) and image-based phenotyping as non-destructive approaches to identify Brachiaria hybrids tolerant to waterlogging stress under field conditions. Nineteen promising hybrid selections from the breeding program and three commercial checks were evaluated for their tolerance to waterlogging under field conditions. The waterlogging treatment was imposed by applying and maintaining water to 3 cm above soil surface. Plant performance was determined non-destructively using proximal sensing and image-based phenotyping and also destructively via harvesting for comparison. Image analysis of projected green and dead areas, NDVI and shoot biomass were positively correlated (r ≥ 0.8). Our results indicate that image analysis and NDVI can serve as non-destructive screening approaches for the identification of Brachiaria hybrids tolerant to waterlogging stress.