Multicollinearity and outliers are common issues in multiple linear regression models. A new method called weighted ridge least trimmed squares (WRLTS) is proposed to address these problems. WRLTS outperforms other methods like Ordinary Least Squares (OLS) and Ridge Regression (RR) in terms of Standard Error. Two examples using R programming show that WRLTS is the most accurate estimator among the methods tested.