Also known as a feature importance chart in data science, the driver rankings chart for a propensity or regression model shows the relative importance of each independent variable in generating a model prediction. It can be loosely interpreted as the share of variance explained by the model that can be attributed to a specific independent variable.

In practice it is a helpful way to rank which drivers (independent variables) contribute most to a model prediction on average.