Rabindra Nritya is one of the famous cultural music and dance forms of West Bengal and is most important India’s cultural heritage. As we are moving toward advancement, it is necessary to keep preserved our heritage for future references. There is a need for documentation and preservation of traditional dance forms and culture in India. The paper focuses on the use of latest technology for the global preservation, protection, and digitization of music and dance, with a specific emphasis on Rabindra Nritya. The study also examines that there is a need of Government of India’s initiative to facilitate us by providing financing aids. It helps to promote Rabindra Nritya globally by organizing events and exhibiting in international festive, forums, etc. There is a need to make more efforts for GIS tags for Rabindra Nritya and to digitize all dance forms, the motions, expressions, and emotions. This paper focusses upon the various latest techniques and technologies which can be used to preserve and protect these traditional dance forms. The paper explores the role of technology in preserving cultural forms and preventing their decline. This research highlights the importance of using machine learning and artificial intelligence in preserving and digitizing cultural traditions. In the phase-I of the research, this paper discussed about the developed image classification model using deep learning methodology to identify and classify different Indian dance forms. Various AI-ML technologies used in this research work are Convolutional Neural Network (CNN), transfer learning models VGG19, ResNet, Inception-v3, and Support Vector Machines (SVMs). The study examines after comparing each model, the most effective model to classify the images with higher efficiency. The other algorithms which are discussed to be used in future for classification and meta tagging are K-Means with LSTM and Decision Tree. This is the primary study and in future research work directs the use of real-time Motion Capture technologies, AR, VR techniques, GIS tagging, and use of Explainable AI (XAI) to classify intricate dance postures. And primary research to test Hypothesis defined for further validation.