The article discusses how regression models can be used to predict future cases, like diagnosing illnesses or assessing risks. It explains that future values of a variable tend to be closer to the average than predicted. This shrinkage effect is more pronounced with small sample sizes or many variables. The study shows that the accuracy of predictions can be affected by how well the original regression model fits the data. Two examples are used to illustrate how predictors can shrink. The article suggests a more general approach to address this issue.