Abstract: Medicine is, in its essence, decision-making under uncertainty. Decisions about the tests to be performed and interventions, pharmacological or surgical, to be administered. These decisions have to be made probabilistically due to uncertainty resulting from the complexity of the human body, a complex system made of a vast number of elements intensely interacting with each other in a non-linear manner. The human body’s complex structure is responsible for millions of unique combinations of risk factors and protective characteristics that individually define our health and disease. It also leads to redundancies within the human body, which result in our robustness to disease and rarity of the essential severe adverse outcomes, such as death. Unfortunately, rare events are difficult to predict and prevent. However, the computation is very well suited to modeling both vast numbers of unique combinations of risk factors and protective characteristics, the individualization of medicine, and the modeling of rare events. These advantages of computational medicine promise to simultaneously improve health outcomes and lower healthcare costs through computationally driven individualization of medicine.