The article compares different estimators based on the principal component two-parameter estimator using the prediction mean square error criterion. It looks at estimators like ordinary least squares, principal components regression, ridge regression, Liu estimator, r-k estimator, and r-d estimator. The study identifies conditions where the principal component two-parameter estimator outperforms the others. A numerical example study is conducted to compare these estimators based on the prediction mean squared error criterion.