Mental health has been discussed more frequently in recent years, especially due to the pandemic. According to the CDC (Centers for Disease Control and Prevention), 1 in 5 Americans will experience a mental illness in a given year. However, there is a stigma around mental health, which often causes issues to go untreated, leading to more severe symptoms and other repercussions, which affect one’s work and personal life. This is why it is important that more research be done in the field in order to address mental health issues in a positive and productive way. Currently, companies provide limited resources, which are insufficient for employees to work through improving their conditions. In this project, I am researching current mental health treatment options and the level of support provided by companies. I am surveying employees, predominantly in the tech industry, regarding the status of their mental health and/or the support they may receive. Finally, I am building three types of machine learning models (1) a logistic regression model, (2) a neural network, and (3) a random forest. The models can be used to determine whether companies provide enough support for their employees’ mental health needs. The goal of this project (and my final product) is to use the results of these models to assist companies in determining the amount of resources they need to provide their employees to improve their mental health.