Computational modeling of developmental processes and morphogenesis is challenging due to the need for cross-comparison between spatial features in experimental data and modeling outputs. In this talk, I will discuss my lab's efforts to derive quantitative metrics that can be used for parameter optimization and model evaluation of stem cell differentiation in 2D and 3D contexts and our resulting simulations and insights using off-lattice agent-based models. Furthermore, I will discuss our novel tools for near-single cell spatial characterization of metabolic processes that correlate, and potentially drive, differentiation.