In today's fast-paced world, mental health concerns that include anxiety, depression, and stress have become quite frequent among individuals of all ages. One of the major reasons behind this problem is the lack of awareness among the masses. Mental health refers to one's psychological, emotional, and social well-being, and it is essential at all stages of life, from childhood and adolescence to maturity. In this study, machine learning algorithms were used to predict anxiety, Depression, and stress. To apply the machine learning algorithms, information was gathered from people of different ages, occupations, sexes, and lifestyles through a questionnaire with questions psychologists frequently use to comprehend their patients' issues in specifics. The results reveal that the model has a high level of accuracy in predicting mental health outcomes. Our aim with this paper is to raise awareness and make people aware that they may be suffering from mental health disorders like Anxiety, Depression, and Stress. The model developed in this study can assist healthcare providers in identifying patients at high risk of developing Mental issues and can enable early intervention and prevention strategies. We believe establishing such a system into effect could help us avoid a future "Mental health epidemic" and make diagnosis easier for people.

Keywords : Anxiety, Depression, Decision Tree Algorithm, Mental Health Prediction, Machine Learning, Stress.