Entropy, a concept derived from thermodynamics and information theory, describes the amount of uncertainty and disorder within a system. Self-organizing systems engage in a continual dialogue with the environment and must adapt themselves to changing circumstances to keep internal entropy at a manageable level. We propose the entropy model of uncertainty (EMU), an integrative theoretical framework that applies the idea of entropy to the human information system to understand uncertainty-related anxiety. Four major tenets of EMU are proposed: (a) Uncertainty poses a critical adaptive challenge for any organism, so individuals are motivated to keep it at a manageable level; (b) uncertainty emerges as a function of the conflict between competing perceptual and behavioral affordances; (c) adopting clear goals and belief structures helps to constrain the experience of uncertainty by reducing the spread of competing affordances; and (d) uncertainty is experienced subjectively as anxiety and is associated with activity in the anterior cingulate cortex and with heightened noradrenaline release. By placing the discussion of uncertainty management, a fundamental biological necessity, within the framework of information theory and self-organizing systems, our model helps to situate key psychological processes within a broader physical, conceptual, and evolutionary context.