Abstract: The quasi-steady state model of temperature profile for the reverse flow reactor with catalytic combustion of air contaminated with volatile organic compounds (VOCs), is developed by RBF (radial basis function) neural networks. The deep knowledge repository of temperature profile is yielded based on a large number of numerical solutions of the determinant mathematical model, which increases the “extrapolative ability” and “reliability”. Simulation results have proved that the model presented in this paper is simple, highly accurate and can satisfy the prediction requirements.