<p>In distribution theory, several classes of classical and bayesian distributions have been formulated to give more flexibility when modelling true characterizations of real-life data. Nevertheless, modelling these true characterizations of real-life data depend on the flexibility of the statistical distribution employed in the process. Hence, a new three Gompertz flexible generated (GF-G) family of distributions of an interest to researchers is introduced to capture the true characteristics of the inherent stochastic processes such as an electrical current fluctuation due to thermal noise, the movement of a gas molecule, and growth of a bacterial population. The new model exhibits an increasing, right and left skewed, decreasing, and unimodal a bathtub shape. Some characterizations of the Gompertz flexible generated model were examined. Maximum likelihood method was adopted in its parameters estimation. A multi-component reliability characterization was explored in this study. The proficiency and efficiency of the GF-G model was investigated using simulated data and real-life data applications. The applications shown the GF-G models performed better when compared to the traditional Gompertz generalized models.</p>