International Science Community Association Research Journal of Mathematical and Statestical Sciences 13 3 2025 09 12 New Ridge Parameters for Generalized Ridge Regression 1 13 EN Dorugade A. V. 1 Y.C. Mahavidyalaya, Halkarni, Tal- Chandgad, Kolhapur, MS - 416552, India > Research Article 2025 4 19 2025 09 12 In Classical Linear Regression, in the presence of multicollinearity there are several methods to get rid of this problem and one of the most famous one is the ridge regression. In this paper, a new procedure to estimate the ridge parameters for Generalized Ridge Regression (GR) estimator is presented. We compared our estimators with other 30 estimators proposed elsewhere earlier according to mean squared error (MSE) criterion. All results are calculated by a Monte Carlo simulation. According to simulation study, our estimators perform equivalently to the estimator under the influence of multicollinearity. Also perform better than the others in the sense of MSE. Copyright@ International Science Community Association