To design today’s complex, multi-disciplinary systems, designers need a design method that allows them to systematically decompose a complex design problem into simpler sub-problems. Systems engineering provides such a framework. In an iterative, hierarchical fashion systems are decomposed into subsystems and requirements are allocated to these subsystems based on estimates of their attributes. In this paper, we investigate the role and limitations of modeling and simulation in this process of system decomposition and requirements flowdown. We first identify different levels of complexity in the estimation of system attributes, ranging from simple aggregation to complex emergent behavior. We also identify the main obstacles to the systems engineering decomposition approach: identifying coupling at the appropriate level of abstraction and characterizing and processing uncertainty. The main contributions of this paper are to identify these short-comings, present the role of modeling and simulation in overcoming these shortcomings, and discuss research directions for addressing these issues and expanding the role of modeling and simulation in the future.