In recent years, the Weibull distribution has been commonly used and recommended to model the wind speed. Therefore, many estimators have been proposed to find the best method to estimate the parameters of the Weibull distribution. Particularly, the estimator based on regression procedures with the Weibull probability plot are often used because of its computational simplicity and graphical presentation. However, when the procedure is applied, in many cases heteroscedasticity or non-normality of the error terms may be encountered. One way to handle this problem is using transformation techniques. In this study, the regression estimation based on data transformation is considered to estimate the parameters of the Weibull distribution. The simulation results show that the considered estimator based on the data transformation for the shape parameter of the Weibull distribution provides better performance than least squares estimator in terms of bias and mean square errors for the most of the considered cases.