The pyrolysis of biomass is a complex process in terms of the kinetic and mass and heat transfer phenomena, which is necessary information for process optimization and large scale modeling. In this paper, an analysis of pyrolysis of sawmill residues is performed in a lab-scale pyrolysis unit to minimize the heat and mass transfer effects. Three factors, including pyrolysis temperature, feedstock particle size, and nitrogen flow rate, in the reactor are optimized using response surface methodology. Two factor-based models (a three factor quadratic model and a quadratic model without factor interactions coefficients) and two kinetic models (one based on primary reactions only, the second including secondary reactions) are compared. The factor-based models (with and without interactions) were developed using design of experiment software and Genetic Algorithm, respectively. The results showed that the quadratic model with interactions between factors predicts the experimental data more accurately compared to the other models. However, the quadratic models are experiment specific and can only be used as a design tool. The primary kinetic model predicts the experimental data trend below 550 degrees C well; however, as temperature rises (>550 degrees C), including secondary reactions gives better predictions.