As flood frequency analysis (FFA) is an exact and vigorous zone of analysis in statistical hydrology, so, in this regard, numerous probability models, parameters estimation procedures, regionalization problems, and other associated issues are being scrutinized in statistical hydrology. For this reason, research on FFA has been conducted with fluctuating passion over the past couple of decades. Therefore, there is a need to introduce flexible probability models and their parametric estimation techniques in statistical hydrology. However, for accurate probability modeling of upcoming flood events researchers try their best to study the heavy tailed distributions. In light of this, we intend to put forth a flexible probability model that not only addresses the problems with regional flood statistics but also illustrates the reasonable return periods for flood events brought on by melting glaciers and rising temperatures. We have described and examined some mathematical and statistical aspects of the suggested approach in light of the aforementioned scenario, and we have used it on actual flood data sets. To ensure realistic predictions using the proposed model, we have also analyzed it in terms of Mellin transformation.