Black males with mental health diagnoses face substantial barriers to gaining and maintaining employment. Tailored employment support services may help increase employment access, yet utilization remains low among this demographic area. The purpose of this quasi-experimental study is to explore the employment challenges for Black males with mental health diagnoses in the US. This quantitative study will utilize a data mining approach drawing from an ex post facto national rehabilitation services dataset. Archival data will be extracted from the Rehabilitation Service Administration 911 (RSA-911) database. Descriptive statistics will first profile the extracted sample of vocational rehabilitation clients on demographic variables. The primary analysis will apply a complex partitioning technique known as Chi Square Automatic Interaction Detection (CHAID) modeled in SPSS Modeler 24.0. Follow-up binary logistic regression will provide individual odds ratios for the prominence of key client, rehabilitation services, and environmental variables in relation to securing employment. The study established that various types of interventions like occupational/vocational, on the job, job readiness training, and job placement services are crucial in determining the employment outcomes. The analysis showed that entry-to-work supports are time-limited, and the identification and treatment of disabilities also improve the mental health care and employment prospects. The work also showed that traditional vocational rehabilitation services alone do not meet these clients' needs. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]