This study aims to develop an approach for predicting crop yields using agrometeorological monitoring software. The Tambacounda region in eastern Senegal, 460 km from Dakar, is at the heart of this research. Geographically, it is the largest of Senegal’s eleven regions. Due to its low population density (14 inhabitants per square kilometre) and its economy, which lags behind the rest of the country, this region presents unique agricultural challenges. The practical laboratory work carried out in the region involved collecting agricultural and meteorological data, as well as satellite images. Phenological variables were extracted and NDVI calculated using the SPIRIT tool. Meteorological data were analysed using the Agromet-shell (AMS) tool, and sorghum yield for 2015 was predicted using the CGMS tool. MODIS/006/MOD13Q1 satellite images from 2012 and 2015 were used for a better graphical representation of the time profiles of the Normalized Difference Vegetation Index (NDVI). The yield explanatory variables showed higher rainfall in Tambacounda in 2015 (around 100 mm) compared with 2012 (a decade of more than 62 mm of rain). The water satisfaction index was 85% in 2012 and 92% in 2015, indicating favourable conditions for a good harvest in the region. Our model predicts a probable yield of 1076.94 kg/ha for 2015, with a margin of error of 191.13 kg/ha (RMSE). This value is close to the average yield observed by the CGMS Statistical tool over the past 14 years (1278.08 kg/ha). This research adds to our understanding of the factors influencing crop yields in Tambacounda. The results can guide agricultural decision-making and advice, and contribute to the existing body of knowledge on crop water balances and the selection of potential yield explanatory variables. They also highlight the importance of using agrometeorological tools for sustainable agriculture in similar regions.