**Decision theory** (or the **theory of choice** not to be confused with choice theory) is the study of an agent's choices.^{[1]} Decision theory can be broken into two branches: normative decision theory, which analyzes the outcomes of decisions or determines the optimal decisions given constraints and assumptions, and descriptive decision theory, which analyzes *how* agents actually make the decisions they do.

Decision theory is closely related to the field of game theory^{[2]} and is an interdisciplinary topic, studied by economists, statisticians, data scientists, psychologists, biologists,^{[3]} political and other social scientists, philosophers,^{[4]} and computer scientists.

Empirical applications of this rich theory are usually done with the help of statistical and econometric methods.

A general criticism of decision theory based on a fixed universe of possibilities is that it considers the "known unknowns", not the "unknown unknowns"^{[citation needed]}: it focuses on expected variations, not on unforeseen events, which some argue have outsized impact and must be considered – significant events may be "outside model". This line of argument, called the ludic fallacy, is that there are inevitable imperfections in modeling the real world by particular models, and that unquestioning reliance on models blinds one to their limits.