Lignin, the major phenolic polymer made by plants, is the main barrier to the utilization of biomass for energy, papermaking, and forage digestibility. Understanding the fundamental nature of lignin biosynthesis will lead to improved crop yields and could also aid in their resistance to drought, pests, and pathogens. Several models, based on mass action kinetics, have been developed to describe how the lignin pathway in plants is regulated and potentially revealed new control mechanisms leading to lignin polymers. Although these models can be accurate, they require significant experimental data to determine the activation and inhibition kinetics, which may be challenging to collect. An alternative approach to these mass action based models is a Boolean derived model. An advantage of this model is that a fairly accurate numerical representation of the biological pathway can be developed from knowledge of substrate/enzyme interaction of various metabolites within the biosynthesis pathway. In this research, a Boolean model was developed to simulate the lignin biosynthesis pathway. This model incorporated a continuous Boolean equation to explain the rate change of the metabolite concentration. Parameters for the continuous Boolean model were obtained by minimizing the Sum Squared Errors (SSE) between the data obtained from the Boolean model and a model based on the Michaelis Menten (M-M) approach using an optimization algorithm. The results from the optimized Boolean model will help explain the preferred flux pattern and also identify the important metabolites necessary for the production of lignin inPopulustrichocarpa.