R^2, or the coefficient of determination, is a statistical measure that explains how well a model predicts outcomes. It ranges from 0 to 1, where 0 indicates that the model does not explain any variability in the data, and 1 means it perfectly explains the variability. A higher R^2 value suggests a better fit of the model to the data. In regression analysis, R^2 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 engineering to evaluate the effectiveness of predictive models.