Neuroeconomics explores the neurobiological and computational basis of value-based decision-making. It aims to provide a biologically grounded account of human behavior applicable to both natural and social sciences. The review proposes a framework to integrate recent findings, highlight key challenges, define a common terminology, and guide future applications. Value-based decision-making is prevalent in nature, occurring in both simple animal behaviors and complex human decisions. Neuroeconomics studies the computations the brain uses to make these decisions and their neural implementation. It combines models, tools, and techniques from economics, psychology, neuroscience, and computer science. The framework divides decision-making into five types of computations: representation, valuation, action selection, outcome evaluation, and learning. These processes involve identifying internal and external states, assigning values to actions, comparing values, evaluating outcomes, and learning from feedback. The review also discusses three valuation systems: Pavlovian, habitual, and goal-directed. Pavlovian systems assign values to evolved responses, habitual systems learn from repeated actions, and goal-directed systems evaluate outcomes. Each system has distinct neural bases and computational properties. The review highlights open questions about how these systems interact, how they incorporate risk and uncertainty, and how they handle long-term goals and moral considerations. It also addresses modulators of valuation systems, such as risk and temporal delays, and the role of the brain in learning and decision-making. The review concludes that neuroeconomics has significant potential in psychiatry, law, public policy, and artificial intelligence, offering new insights into decision-making processes and their applications.Neuroeconomics explores the neurobiological and computational basis of value-based decision-making. It aims to provide a biologically grounded account of human behavior applicable to both natural and social sciences. The review proposes a framework to integrate recent findings, highlight key challenges, define a common terminology, and guide future applications. Value-based decision-making is prevalent in nature, occurring in both simple animal behaviors and complex human decisions. Neuroeconomics studies the computations the brain uses to make these decisions and their neural implementation. It combines models, tools, and techniques from economics, psychology, neuroscience, and computer science. The framework divides decision-making into five types of computations: representation, valuation, action selection, outcome evaluation, and learning. These processes involve identifying internal and external states, assigning values to actions, comparing values, evaluating outcomes, and learning from feedback. The review also discusses three valuation systems: Pavlovian, habitual, and goal-directed. Pavlovian systems assign values to evolved responses, habitual systems learn from repeated actions, and goal-directed systems evaluate outcomes. Each system has distinct neural bases and computational properties. The review highlights open questions about how these systems interact, how they incorporate risk and uncertainty, and how they handle long-term goals and moral considerations. It also addresses modulators of valuation systems, such as risk and temporal delays, and the role of the brain in learning and decision-making. The review concludes that neuroeconomics has significant potential in psychiatry, law, public policy, and artificial intelligence, offering new insights into decision-making processes and their applications.