When the interdependence of disturbances is present in a regression model, the pattern of sample residuals contains information which is useful in the prediction of post-sample drawings and when multicollinearity among regressors is also present, it is useful to use biased regression estimators. This information is exploited in the biased predictors derived here. Also, the predictive performance of various biased predictors with correlated errors is discussed and all pair-wise comparisons are made among these predictors. The theoretical results are illustrated by a numerical example. Copyright (c) 2015 John Wiley & Sons, Ltd.