This paper investigates the inverse and power Juchez distribution. Some relevant properties are studied, and the distributions can altogether model many varieties of datasets emanating from different life phenomena. And then, a generator for other generalized distributions termed Juchez-G is developed to suffice for the relevance of robust model development. Finally, IJD and PJD showed to be a better fit over both the baseline distribution and their respective counterpart distributions, with respect to the datasets used. The proposed method is interesting and the performance is superior.