This research paper reviews the publication trends of the Web of Science(WOS) and Scopus databases from 2020 to 2023 topics related to the prediction of COVID-19 numbers in India. Through bibliometric analysis, we investigate trends in publications and citations of COVID- 19, highly cited papers, most frequent authors, and their affiliated institutions and network visualisation is performed using various types of analysis, i.e. co-authorship of authors, co-occurrences of keywords, bibliographic coupling, and co-citation of cited sources. Various biometric tools has been analysed Citations per publication(C/P), Cited Publications (CP), citation density and the finding of the study indicate that lots of research has been done during this period (2020-23) on the prediction of COVID-19 using machine learning and deep learning techniques. Useful insights in the findings provide greater chances to explore more in the field of prediction of the spread of viruses using machine learning techniques.