In today’s time and budget intensive software development market, quick delivery is the basicmotive of teams. Software development teams strive to gain customer satisfaction by allpossible means. Requirements prioritization is the most challenging customer input dependenttask in the software development life cycle that decides the fate of a project. Selection of awell-suited requirements prioritization technique may result in customer satisfaction and ontime delivery time. Literature reports on many requirements prioritization techniques inpractice. However, each has its own features that can outperform the rest for a certain case.Therefore, this research is conducted to empirically evaluate the existing techniques in termsof certain quality measures (i.e., accuracy, efficiency, and scalability). The selected techniquesare evaluated for the small, medium and large scale of requirements sets. For that, we selectedfive existing techniques that are multi-criteria-decision-making techniques and have userinvolvement (i.e., Analytical Hieratical Process (AHP), Analytical Network Process (ANP),FuzzyAHP, FuzzyANP and Interactive Genetic Algorithm (IGA)). The experimental resultsshowed that among the five selected techniques, FuzzyAHP is the most efficient and accuratetechnique for the large dataset of requirements.