Cotton yields in the Sudano-Sahelian region contribute to food security through their role in agricultural productivity. Daily precipitation data and cotton yield data were synthesized from nine agricultural regions obtained from the “Société de Développement du Coton (SODECOTON)”. The following seasonal rainfall indices—from Cameroon’s cotton zone—were mapped with geographic information systems for spatial analysis: wet season onset and retreat date, rainfall amount, number of rainy days, rainfall intensity (SDII), heavy-rainfall events (R95p), consecutive dry days (CDD), annual highest daily precipitation (Rx1day) and number of very heavy precipitation days (R20mm). Linear regressions were used as statistical tools for analysis. The strongest relationships were observed between cotton yields and the heavy-rainfall events, closely followed by seasonal rainfall amount. An increase in consecutive dry days (CDD) and heavy events, and a decreased seasonal rainfall amount, have a negative impact on cotton yield trends. Overall, the critical breakpoint analysis between cotton yields and all rainfall indices showed that the cotton yield was particularly negatively impacted before a 251 retreat date, 591 mm seasonal rainfall amount and 33 rainy days. By contrast, an onset date, rainfall intensity, heavy rainfall, CDD, Rx1day and R20mm of 127, 12.5 mm·day−1, 405 mm, 27 days, 67 mm and 22 days, respectively, were identified for an optimum cotton yield. These results can be used as information for agricultural activity and management, civil planning of economic activities and can also contribute to furthering our understanding of the management impacts on future food security.