We study the re-parameterized length-biased inverse Gaussian distribution based on [1]. We propose an alternative to estimators with the method of moments and the maximum likelihood method in a closed-form expression. We compare the effectiveness of estimators with the method of moments and the maximum likelihood method using mean squared error (MSE), and Bias. Moreover, we use the R package “ELBIG” for the parameter estimation for re-parameterized length-biased inverse Gaussian distribution with two estimation methods: the maximum likelihood method, and the method of moments. Furthermore, we illustrate with an example the real data for the proposed estimators. The results show that the parameter estimation of re-parameterized length-biased inverse Gaussian distribution using the method of moments and the maximum likelihood method produces a consistent estimator and the maximum likelihood estimators