The article reviews different robust statistical methods used to estimate regression credibility. These methods are more reliable when dealing with outlier events in the data, like large claims or catastrophic events, which can affect traditional estimation techniques. The reviewed estimators include L1, M, GM, LMS, LTS, S, MM, and robust REWLS estimators. These robust estimators are better at handling extreme data points and provide more accurate credibility premium estimates in regression analysis.