The design of optimal bioreactor systems for tissue engineering applications requires a sophisticated understanding of the complexities of the bioreactor environment and the role that it plays in the formation of engineered tissues. To this end, a tissue growth model is developed to characterize the tissue growth and extracellular matrix synthesis by chondrocytes seeded and cultivated on polyglycolic acid scaffolds in a wavy-walled bioreactor for a period of 4 weeks. This model consists of four components: (1) a computational fluid dynamics (CFD) model to characterize the complex hydrodynamic environment in the bioreactor, (2) a kinetic growth model to characterize the cell growth and extracellular matrix production dynamics, (3) an artificial neural network (ANN) that empirically correlates hydrodynamic parameters with kinetic constants, and (4) a second ANN that correlates the biochemical composition of constructs with their material properties. In tandem, these components enable the prediction of the dynamics of tissue growth, as well as the final compositional and mechanical properties of engineered cartilage. The growth model methodology developed in this study serves as a tool to predict optimal bioprocessing conditions required to achieve desired tissue properties.