Members of the CCSI Technical Leadership Team recently published an invited article in Power Engineering, which focuses on essential elements related to the development and validation of multi-scale models in order to help minimize risk and maximize learning as new technologies progress from pilot to demonstration scale. CCSI developed a comprehensive, hierarchical model calibration and validation framework, which utilizes Bayesian statistics and other principles of uncertainty quantification, to provide stochastic model predictions that result in a complete probability distribution of expected behavior. The use of this framework is described in the context of two examples: (1) a high-fidelity computational fluid dynamics (CFD) model of bubbling fluidized bed (BFB) adsorber for capturing CO2 on a chemically reactive solid sorbent, and (2) a solvent-based CO2 capture system consisting of a packed bed absorber and packed bed stripper.