The measurement of social progress and well-being has acquired a multidimensional structure, moving beyond traditional economic indicators. Although the "2015 Well-Being Index for Provinces" published by the Turkish Statistical Institute (TurkStat) provides a comprehensive indicator system designed for this purpose, it contains methodological limitations due to the "hierarchical equal weighting" method used in aggregating the dimensions. The assumption of equal weighting ignores the internal variance of the data and the discriminatory power of the indicators, potentially leading to statistical bias in rankings. This study aims to re-evaluate the quality of life rankings of the 81 provinces in Turkey through an objective approach that considers the internal information load of the data. Accordingly, a hybrid Entropy-based TOPSIS method was applied using TurkStat's dataset consisting of 11 dimensions and 41 indicators as a reference. In the first stage, the weights of the life dimensions were calculated in a completely data-driven manner using the Shannon Entropy method; in the second stage, these weights were integrated into the TOPSIS model to obtain a new ranking based on the geometric distances of the provinces to the positive and negative ideal solutions. The entropy analysis revealed that the dimensions with the highest discriminatory power among provinces are "Income and Wealth" (19.80%), "Life Satisfaction" (15.55%), and "Access to Infrastructure Services" (13.07%), while the "Safety" dimension received the lowest weight (2.75%). In the TOPSIS ranking, Istanbul, Ankara, and Izmir, which exhibit strong performances in dimensions with high weights, ranked in the top three, whereas provinces like Isparta and Sakarya at the top of the original index declined, and the position of the disadvantaged provinces at the bottom remained unchanged due to structural problems. In conclusion, this study offers an evidence-based methodological guide for decision-makers to revitalize such one-off national indices on a rational and sustainable basis.