1. Remove Variables: One of the simplest ways to address high VIF is to remove one or more of the correlated variables. 2. Combine Variables: If two or more variables measure the same underlying phenomenon, they can be combined into a single variable. 3. Principal Component Analysis (PCA): This statistical technique can be used to transform correlated variables into a set of linearly uncorrelated variables. 4. Regularization Techniques: Methods like ridge regression can help to mitigate the effects of multicollinearity.