Global climate change, characterised mainly by an upsurge in extreme rainfall events, is affecting the precarious economies of most vulnerable countries. The aim of this study is to analyse extreme rainfall events in the Oti watershed, which is characterised by high climatic variability. Daily observed and simulated rainfall and temperature data from two models (CCLM and REMO) in the Cordex programme were used. The data is subjected to statistical processing methods. Climatic indices were calculated using RclimDex software. The results obtained show a spatio-temporal variability in observed and simulated rainfall that follows an increasing north-south gradient. Both models overestimate observed rainfall, with deviations of 1.95 for the CCLM and 8.53 for the REMO. This shows that the CCLM is more realistic in reproducing observed rainfall, is therefore validated for the rainfall projection. The rainfall indices show a non-statistically significant increase in PRCPTOT, R99p, RX1day, RX5 days and CWD on the one hand, and a decrease in the SDII, R10 mm, R20 mm and R95p indices on the other for the observed rainfall. For simulated rainfall, the RCP 8.5 and RCP 4.5 scenarios predict an upward trend in some indices and a downward trend in others from 2025 to 2069.