The main practical problems caused by multi-collinearity are reviewed. The biased estimators based on the generalization of principal components for avoiding multi-collinearity problems are described. The mean quadratic error of prediction criterion is used for the selection of suitable bias. Some advantages of biased regression are demostrated on the problem of intercept estimation in a polynomial model. © 1993.