Physiology has always followed an integrative approach to gain insight into the functions of the human body. The system approach considers biological processes as systems of interacting components. Mathematical and computational modeling aims to bridge the gap between experimentally gained observations of isolated components and the desired understanding of the whole living organism in health and disease. This approach requires a clear definition of the purpose, the assumptions, and the boundaries of the model. It is necessary that mathematical models have to be based on reliable experimental data. At present we witness an amazing development and refinement of biophysical methods to quantitatively describe biological phenomena with increasing accuracy. In parallel, sophisticated computational techniques enable the increasingly efficient solution of ordinary and partial differential equations, which are used to describe these systems in the language of mathematics. The hierarchical nature of causal knowledge and understanding consequently leads to “multi-scale” modeling, integrating important features across multiple levels of organizational, spatial or temporal scales. Perhaps the most advanced area of computational physiology is computational cardiac electrophysiology, investigating the electrical activity of the heart. Multi-scale cardiac modeling and simulation have been crucial in improving our understanding of ionic mechanisms of normal and abnormal heart rhythm, electrotherapy, and the electrocardiogram.