Predictive modeling tools have the potential to accelerate the development and deployment of biomass thermochemical conversion. Considerable progress has been made in the modeling of biomass pyrolysis at the particle level, where chemical kinetics and transport processes are coupled. However, rigorous validation of the corresponding models is challenging because of the considerable uncertainty in the values of several biomass properties. Toward this end, we use the principles of uncertainty quantification (UQ) for a rigorous analysis of the validity of a commonly used one-dimensional wood pyrolysis model. Uncertainty in the modeling parameters of the transport processes is propagated to the simulation results of the pyrolysis model. The model predictions are compared with several detailed experimental measurements for pyrolysis of wood particles. The results show that the uncertainty in the model predictions account for some of the discrepancies with the experimental measurements, especially for the particle temperature profiles and the gas phase species production rates. Experimental targets are identified whose predictions cannot be improved by an accurate knowledge of the transport model parameters and require further improvements in the chemical kinetics model. The use of a systematic optimization technique is also demonstrated to choose the optimal values of uncertain model parameters. © 2018 American Chemical Society.