Resumen: The predictive system developed in this Thesis has the same structure as the so-called combustion kinetics models, however, it obtains the fluid and thermal description through CFD simulations. To solve the handicap of the high computational cost needed to run a CFD simulation, a neural network system is used to reproduce the solutions given by the CFD code. Moreover, a neural network system permits to interpolate in the range of variation used during the training stage, and thus, a predictive system covering the whole operational range of the plant is obtained.