The article introduces new ridge estimators to handle multicollinearity and heteroscedasticity in data. These improved estimators reduce mean square error compared to existing methods, especially with highly collinear and heteroscedastic data. They are easy to use and offer a simple solution to both issues at once. Through simulations and real data applications, the new estimators have been shown to outperform existing ones.