This paper describes a capstone project that investigated automated methods to assist the mapping of problem list terms to the SNOMED CT terminology. Building on the previous work of Dr. Francis Lau, a database schema and associated matching algorithms were developed and tested. A methodology of recommended matching steps was defined and tested against three different problem list datasets. Associated results and metrics were recorded and areas for improvement and future research were identified. The tools and methodology developed during the project were found to be effective in the mapping of diverse problem list datasets to the SNOMED CT terminology.