Abstract: For an estimation of the ridge parameter, relevant research on estimation methods released from 1964-2014 has been reviewed and new estimation methods are suggested in this study. The history of multicollinearity dates back to 1934 when the multicollinearity concept was formulated to refer to the condition when the variables handled are under influence of two or more relationships. To tackle this type of problem, another study proposed Ridge Regression (RR). By that time the aim was mainly to identify value of the ridge parameter, k, such that reduction in the variance term of the slope parameter is larger than the increment in its squared bias. Furthermore, non-zero values of the ridge parameter for which the Mean Squared Error (MSE) of the slope parameter is less than the variance of the Ordinary Least Squares (OLS) estimator of the very parameter has been proven using RR. Thus, various estimations of the RR parameter have been improved and related estimation methods suggested by a number of researchers working in this field of scientific research.