Humid heatwaves, characterized by high temperature and humidity combinations, pose significant challenges to tropical societies. Recent research has shown that extreme wet-bulb temperatures (TW) in tropical regions are coupled to the warmest sea surface temperatures (SST) due to unique atmospheric dynamics. In this study, we investigate the potential of using this mechanism for seasonal forecasts of the annual maximum of daily maximum TW (TWmax). To achieve this, we develop a multiple linear regression model that explains 80% of the variance in tropical mean TWmax and a substantial portion of regional TWmax variability. The predictive model considers both cumulative warming trends and preceding El Niño and Southern Oscillation (ENSO) indices, with each contributing similarly to the explained variability of TWmax. Looking ahead, the combination of a strong El Niño event with the current level of accumulated warming raises the likelihood of setting new tropical land mean TWmax records in the following year to about 50%. This forecasting approach holds promise in assisting tropical societies to proactively prepare for and manage the impacts of extreme humid heatwaves.