Zambia and Malawi are rated as two of the most vulnerable countries to climate change, while smallholder tilapia farmers lack the expertise and resources to implement mitigation strategies in response to adverse weather conditions. Among climate-driven environmental stressors, such as water supply and temperature variability, temperature can cause production loss and poor physiological performance of tilapia in the short term. Pond temperature fluctuations beyond favourable production conditions need to be foreseen and managed in advance. Through WorldFish, an air-water temperature relationship algorithm for pond water temperature forecasting was developed to be integrated with the iSAT data hub and an early temperature warning decision tree matrix. The decision tree matrix will be developed into a dashboard based on input data and water-quality parameter thresholds for critical scenarios for tilapia and catfish. To mitigate the impact of high-risk (24 and 32 °C for minimum and maximum temperatures, respectively) and emergency (12 and 40 °C) scenarios on cultured stock, a color-coded alarm corresponding with a specific action protocol for pond temperature regulation is activated once predicted pond temperatures approach temperature thresholds. In each case, the messages include information about the current temperature, predictions, the impact of temperature on fish health, monitoring parameters, monitoring frequency, and mitigation steps. The prediction tool’s early warning system is based on pond temperature thresholds derived from mean pond temperatures. It is however important to note that normal pond temperatures between 12 and 18 °C are not optimal for tilapia growth and feed conversion efficiency. A temperature-based early-warning alert system can significantly enhance the resilience and productivity of fish farming in Zambia and Malawi by providing farmers with timely information to adapt to environmental challenges. This system would not only help in managing risks associated with extreme temperatures but also contribute to the overall sustainability and growth of the aquaculture sector in these regions. Future work will focus on the development of priority low-cost pond monitoring equipment for temperature, oxygen levels, and pH, that can store data in an online database. Additionally, hydrological data for surface waters and pond water replacement rates needs to be integrated.