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Abstract: It is been observed that during the COVID-19 pandemic, schools and colleges were forced to close, and many students have experienced severe or mild symptoms of mental health disorders. Mental illness is a disorder characterized by anxiety, depression, and stress. It is becoming more prevalent due to the increasing number of health problems. In this paper, we aim to conduct a timely assessment of the effects of the COVID-19 pandemic on the mental health of students. This research work proposes to get user inputs and display results about how good or badly has the pandemic affected the mental health of the person. The dataset used is related to social life and mental health of students, it will help raise awareness among them and provide greater attention to work related stress, depression and proper benefits can be provided to students suffering from a mental illness. The data used contains different labels such as age, Mode of online classes, time spend on fitness, self-study, sleep etc. Decision Tree classification algorithm was applied for classification of the data as it was found to be more accurate. The research presents an analysis of applying the aforementioned machine learning algorithm on the target groups and also suggests directions for future work. Keyword- COVID-19, Decision Tree classification, Machine learning, Mental Health, Students.