This article unveils an innovative approach to improving the entropy measure analysis of Decision Making Units(DMUs) in the context of linear Diophantine multi-fuzzy soft sets. Though multi-fuzzy soft sets combine multi-dimensional values and parameters to create a hybrid model with considerable versatility, linear diophantine fuzzy sets, a noteworthy extension of conventional fuzzy sets, are also utilized to ease prior constraints. Entropy is a fundamental concept in fuzzy set theory and a useful tool for quantifying the level of fuzziness seen in fuzzy sets. We employ entropy measurements to quantify the weights of input and output components in data envelopment analysis, a non-parametric method frequently used in multi-criteria decision-making. The novelty of this study is integrating the weight determination in Data Envelopment Analysis (DEA) by introducing novel entropy measures with linear Diophantine multi-fuzzy soft sets. The significance of DEA is found in its strong analytical capabilities, which facilitate improved decision-making, boost operational effectiveness, and encourage ongoing development in a variety of industries. To illustrate the significance of our suggested approach, we offer a numerical example of building energy efficiency using a DEA model. This work contributes to fuzzy set theory and DEA techniques, offering a helpful tool for evaluating and enhancing complex decision systems.