Abstarct: In this project considers several estimators for estimating ridge regression estimators in singular linear model. In order to tackle the multicollinearity or ill-conditioning design matrices in singular linear model with linear equality restrictions, the conditional ridge-type estimation is proposed and some properties of the estimator are also studied. Furthermore, the conditional ridge-type estimation is compared with the restricted least squares estimator, and separate sufficient conditions are derived for the superiority of the new estimator over the restricted least squares estimator in terms of mean squares error and mean squares error matrix . A simulation study has been conducted to compare the performance of the estimators.