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This research study attempted to develop a modular framework for a blended learning management system for the development of industry-fit graduates from educational institutions. The review of literature explored relevant studies and also discussed different classifications of blended learning models. The objective was to reduce the bottleneck that poses educational quality concerns and increase the learner’s retention rate from the delivery mechanism. The instructor’s perspective pertains to where the learner is making use of the learning acquired throughout the learning process such that the instructors of the expert area could make assessments on how they perceive the retained learning in the real-life scenario. A machine learning-based blended learning model is designed to meet the benchmarks set by the academic stakeholders. In addition, a two-pronged approach mechanism has been developed for maximizing the learner’s retention process. An automated system for generating the optimum dossier and mix of delivery modules had also been discussed. Subsequently, the framework would ensure continuous tracking of the capability, ability, retention, and performance of the learner. It will automatically create assessments for the different levels of learners’ clusters and predict recommended learning mechanisms. Therefore, the designed model focussed on continuous quality enhancement along with an intelligent blended learning management system for overall educational development.