Mathematical models are a tool to examine existing theories, find gaps in knowledge and explain phenomena of nutrient digestion and metabolism. The model can then produce simulation data to examine model behavior and determine if predictions from such models make biological ‘sense’. The objective of this session is to explore how concepts or theories of nutrient digestion, metabolism and lactation physiology are translated into mechanistic mathematical equations and combined into a whole animal model using the Molly model. Molly is a mechanistic model of a dairy cow composed of a digestive element and an animal element. The digestive element converts chemical composition of the diet to volatile fatty acids, microbial growth and absorbed nutrients using physical attributes of the diet such as proportions of large and small particles and water passage. The animal element converts products from the digestive element into tissues (protein), waste products, heat production or secreted products (milk, milk fat, etc.). In this session, representations of digesta passage, protein synthesis and milk production in Molly will be examined beginning with a conceptual diagram. Then differential equations representing these processes will be described. Finally, because Molly predicts changes in production processes over time, full lactation simulations will be demonstrated to show examples of how passage, protein accretion and milk synthesis change over time. Based on these examples, participants will conduct a simulation exercise which uses concepts of milk synthesis in Molly that were explored previously to predict lactation performance. A compiled version of the Molly program which operates only in the Windows environment is available for download at http://www.vmtrc.ucdavis.edu/laboratories/metabolic/molly.cfm and will be used in the simulation exercise. In the exercise, participants will observe effects of altering milk production processes on production of the dairy cow to understand how metabolic processes can be represented by mathematical equations to provide a conceptual framework that improves our understanding of animal biology.