R², or the coefficient of determination, is a statistical measure that indicates how well a model explains and predicts future outcomes. It ranges from 0 to 1, where 0 means the model does not explain any variability in the data, and 1 means it explains all the variability. A higher R² value suggests a better fit between the model and the observed data. In the context of linear regression, R² helps assess the strength of the relationship between the independent variable(s) and the dependent variable. It is commonly used in fields like economics, biology, and social sciences to evaluate the effectiveness of predictive models.