Abstract: Uganda faces significant health challenges, including infectious diseases and maternal mortality, prompting the government to integrate digital technologies into its Health Information and Digital Health Strategic Plan (2020/21-2024/25). While applications like MatHelp and Ask RHU have improved access to reproductive health services, there remains a critical need for a personalized medical recommendation system. This study develops a healthcare recommendation system tailored to Uganda’s needs using Content-Based Filtering (CBF) and Case-Based Reasoning (CBR). The CBF approach employs vectorization and cosine similarity to match users with suitable healthcare facilities, while the CBR method, implemented through the Intellikit framework, selects facilities based on structured case representations. Additionally, this work introduces a novel dataset compiled from various online sources and Google Maps API, incorporating key features such as location, operating hours, available medical services, and facility ratings. By leveraging digital technologies to connect users with appropriate healthcare providers, this study contributes to enhancing healthcare accessibility and quality in Uganda.