What practice involves organizing variables to predict an outcome variable effectively?

The practice that involves organizing variables to predict an outcome variable effectively is regression analysis, specifically stepwise regression.

Stepwise regression is a method that automates the process of selecting the most significant predictors from a larger set of variables to improve the model's predictive accuracy. It systematically adds or removes variables based on specific criteria, which helps identify the best subset of variables for predicting the outcome variable while controlling for overfitting and multicollinearity. This technique streamlines predictive modeling by focusing on the most influential predictors, thus optimizing the model's performance.

While regression analysis encompasses a broader category of techniques aimed at understanding the relationship between independent variables and a dependent variable, stepwise regression is a focused method within that category, specifically designed for model selection. Therefore, the selection is appropriate as it emphasizes the process of identifying and organizing variables to enhance prediction efficiency.