Screen reader software plays a critical role in enabling individuals with visual impairments to access digital information, yet selecting the most suitable system remains challenging due to the presence of multiple technical, usability, and accessibility criteria. This study aims to develop a comprehensive decision‐support framework for evaluating and optimizing screen‐reading systems. The proposed framework integrates fuzzy entropy for objective criteria weighting, the gray wolf Optimizer (GWO) algorithm for refining the weights, the Fuzzy MARCOS method for ranking alternatives, and SWOT–TOWS analysis for generating strategic development recommendations. Eleven widely used screen reader systems were evaluated based on twenty criteria, covering technical performance, accessibility features, usability, and long‐term sustainability. The results indicate that compatibility with operating systems, web accessibility, and stability and reliability are the most influential evaluation criteria. The ranking results identify JAWS, NVDA, and VoiceOver as the top‐performing screen reader solutions. Furthermore, the strategic analysis suggests that combining artificial intelligence integration, multiplatform compatibility, and cost‐efficient development strategies provides the most effective pathway for improving future screen reader technologies. The proposed hybrid framework offers a systematic and practical approach for evaluating assistive technologies and provides useful insights to developers, policymakers, and stakeholders working to enhance digital accessibility.
Ibrahim M. Hezam (2026) studied this question.