Trust quantification in multi-cloud electronic medical record (EMR) sharing environments presents complex challenges due to uncertainty, dynamic factors, and sensitive data requirements. This research introduces a novel fuzzy logic-based trust assessment framework that effectively models trust by leveraging linguistic variables, adaptive membership functions, and sophisticated inference rules. By integrating critical trust dimensions such as data security, regulatory compliance, historical performance, and system uptime, the proposed methodology provides a nuanced, context-sensitive approach to trust evaluation. The framework demonstrates significant potential for enhancing security and reliability in healthcare cloud infrastructures by handling imprecision, incorporating expert knowledge, and enabling continuous learning and trust model adaptation. Experimental results validate the approach’s effectiveness in generating meaningful trust scores that capture the multifaceted nature of trust in complex technological ecosystems.