Gasification is extensively used in the biomass utilization industries and can be applied to manage the municipal waste wastes in order to transform solid wastes into a clean syngas. In this work, we developed an artificial neural network (ANN) to simulate the influence of two important hydrodynamic factors, namely, heating rate and gasifier length on hydrogen yield and hydrogen efficiency. Results showed that with the increase of gasifier length, hydrogen yield was increased due to a considerable increase in the rate of reactions with increasing the gasifier length. It was also found that the hydrogen yield reached a constant rate probably due to a significant increase in the heat and mass transfer limitations, especially at the end of gasifier.