The Free Energy Principle (FEP) is a normative computational framework for iterativereduction of prediction error and uncertainty through perceptioneintervention cycles thathas been presented as a potential unifying theory of all brain functions (Friston, 2006). Anytheory hoping to unify the brain sciences must be able to explain the mechanisms ofdecision-making, an important cognitive faculty, without the addition of independent,irreducible notions. This challenge has been accepted by several proponents of the FEP(Friston, 2010; Gershman, 2019). We evaluate attempts to reduce decision-making to theFEP, using Lucas' (2005) meta-theory of the brain's contextual constraints as a guidepost.We find reductive variants of the FEP for decision-making unable to explain behavior incertain types of diagnostic, predictive, and multi-armed bandit tasks. We trace the shortcomings to the core theory's lack of an adequate notion of subjective preference or “utility”, a concept central to decision-making and grounded in the brain's biological reality. We argue that any attempts to fully reduce utility to the FEP would require unrealistic assumptions, making the principle an unlikely candidate for unifying brain science. Wesuggest that researchers instead attempt to identify contexts in which either informationalor independent reward constraints predominate, delimiting the FEP's area of applicability.To encourage this type of research, we propose a two-factor formal framework that cansubsume any FEP model and allows experimenters to compare the contributions ofinformational versus reward constraints to behavior.