The researchers developed a new estimator called NSRTPE to improve predictions in multiple linear regression models with multicollinearity. They compared NSRTPE with other estimators like OLSE and RE, and found it performed better in terms of accuracy. Through simulations and real-world examples, they demonstrated that NSRTPE outperformed existing estimators in reducing errors.