Because of its overarching impact on society, aging has always been a topic of great scientific interest. The human body is capable of self-healing following injury and infection, but the healing is never quite perfect, which leaves microscale alterations to molecular and cellular structures. The slow but gradual accumulation of this microscale damage eventually percolates to the macroscale where it affects the functional performance of tissues and organs. Lung aging contributes significantly to the aging of the organism, and to its susceptibility to disease. While research on aging has mostly focused on the experimental testing of aging hypotheses, modeling has played a major role in unraveling the mysteries of aging. For example, scaling concepts applied to lung aging demonstrate how microscale aging affects macroscale function. This sets the scene for an examination of how aging can be imposed on network models of the parenchyma upon which agent-based models of cellular metabolism operate. Since a living system is a vast network of dynamic interactions, general network approaches are applicable to the question of aging. Increasingly accurate model predictions of lung aging based on its current state and environmental factors may lead to better treatments for age-related diseases.