We propose a new wider family called the weighted Lindley-G family. We derive some mathematical properties and
special sub-models of the new family. We address the estimation of the model parameters by eight approaches of estimation.
The estimation approaches are ranked and compared by using detailed simulations to develop a guideline for choosing the
best approach for estimating the distribution parameters. The potentiality of the new family is illustrated via two applications
to real-life data. It is shown that the proposed WLi-G family is more flexible as compared to some of the most cited families
in the distribution theory literature such as the exponentiated-G, beta-G, transmuted-G, and alpha-power-G families under
the same baseline model.