Most of the existing mathematical models for outdoor biotechnological processes require the measurement of the medium temperature, and therefore, they cannot forecast the process dynamics in the future or perform scenario analysis under different climatology. Fully predictive models are thus required for advanced predictions and optimization of environmental bioprocesses affected by weather fluctuations. This is of major importance for supporting the industries in the bioprocess design, decision making and process management. Here, we introduce the FLAME modelling framework for forecasting the fate of outdoor bioprocesses. It integrates, on top of a biological model conserving carbon, nitrogen and phosphorus, a heat transfer model and a chemical sub-model for computing the speciation of all the dissociated chemical molecules. The versatile FLAME modelling platform includes different modules with balanced complexities. Alternative biological models can easily be interchanged, in order to promote a dialog for bioremediation model comparisons and improvements. The approach is illustrated with an algae- bacteria wastewater treatment pond, subjected to the solar flux and to the meteorological events (wind, rain, ...). The fully predictive model was validated over more than one year, therefore representing all the seasons. The temperature prediction turns out to be crucial, especially to appropriately simulate nitrification. The model estimates the dynamics of the different biomasses in the system, providing a diagnosis tool to follow the hidden part of the process dynamics. The proposed framework is a powerful tool for advanced control and optimization of environmental processes, which can guide the scaling up and management of the most innovative bioprocesses.