Despite myriad mental health programs to address mental illness in place in public schools across the United States, rates of child and adolescent mental illness continue to rise. As an indicator of the severity of these issues, child and adolescent deaths by suicide, among those aged 10 to 24, provide a stark example: this rate increased 56% across the US between 2007 and 2017 (Curtin & Heron, 2019). Children and adolescents face many inequalities in relation to developing mental illnesses which include location, poverty, caretaker mental illness, substance misuse in the home, abuse and neglect (Hair et al., 2015; Marmot et al., 2008; Vernon-Feagans et al., 2012). In addition to increased risk for developing mental illnesses, there are identification and treatment disparities related to location, family demographics and family mental health (Barnett, 2008; Johnson & Coles, 2013). Public schools, which service 90% of children and adolescents in the U.S., (Elementary and Secondary Enrollment, NCES, 2019), present a promising site for the identification and intervention of mental health issues. Unfortunately, there are also barriers in the identification and delivery of mental health treatment. With teacher overutilization, vague state and district-level mental health policies and highly variable resources and staff, schools are providing an inconsistent response to student mental illness (Jacob & McGovern, 2015; Reinke et al., 2011a; Walcott et al., 2018). Some interventions may be more effective than others, and classroom teachers may be able to provide insights into the effectiveness of interventions as they spend the most time observing the effects on their students. The purpose of this research was to collect teachers' perceptions of their school as an environment for supporting student mental health. To this end, I implemented a mixed methods research project to examine school environments as they relate to mental health at the school building, district and county level to ascertain whether certain environments (consisting of mental health staff, programming and policies) were perceived as being helpful to supporting student mental health. First, I collected teacher data using a mixed-methods, cross-sectional electronic survey that included demographic questions, questions about school resources, open-ended questions and a validated instrument for assessing teachers' perceptions, attitudes and emotions related to student mental illness. In addition to this, I gathered data from the US Decennial Census and the National Center for Education Statistics. For policy analysis, I collected data from school districts' board policy manuals. To analyze data, I used a combination of inferential and descriptive statistical models in addition to qualitative thematic analysis. I developed analysis categories for school buildings and districts using hierarchical clustering analysis to compare variables such as staff to student ratios, county financial demographics, district spending and other differences which may impact mental health environments. The three types of categories are mental health policies, school district variables, overall financial variables and school building variables. To assess relationships between categories and the data from surveys and reports, I developed regression models to analyze the likelihood of effects between variables. The purpose of this project was to take a first step to assess whether school differences among these four analysis categories impact student mental health.