When the coronavirus first appeared, it has been more and more challenging to obtain suitable therapeutic resources, such as the lack of specialists and other medical professionals, the right tools and medications, etc. The fact that the medical industry as a whole is in disarray is responsible for several deaths. Many started taking medication on their own without the required consultation due to a lack of availability, which worsened their health conditions. Nowadays, machine learning has shown to be effective in a number of situations, and automation-related creative work is growing. This essay aims to propose a system for prescribing medications that can significantly lessen the workload specialised group. In this research, we created a top and alternate drug recommendation system that uses patient feedback to forecast sentiment using a variety of vectorization techniques like Bow, which can aid in recommending the best medication for a particular ailment by using the LGBM Classifier algorithm.