This chapter offers a comprehensive overview of teleophthalmology and its evolution as a transformative part of digital eye care, emphasizing the role of artificial intelligence (AI) in expanding access, enhancing diagnostic accuracy, and improving disease management. It traces the historical development of teleophthalmology from early image transmission technologies to modern applications driven by 5G connectivity, smartphone-based imaging, and AI-powered diagnostics. In various ophthalmic subspecialties, such as anterior segment disease, glaucoma, diabetic retinopathy, age-related macular degeneration, pediatric ophthalmology, and neuro-ophthalmology, teleophthalmology has proven effective in both asynchronous (store-and-forward) and synchronous (real-time) models. Deep learning (DL) algorithms now enable autonomous screening for diabetic retinopathy and retinopathy of prematurity, while machine learning (ML) improves remote glaucoma and cataract assessment. The integration of mobile imaging, cloud platforms, and AI-based decision support systems has increased accuracy and access, especially in underserved and remote areas. Despite these progressions, challenges remain in clinical validation, standardization, and data governance. Ethical issues, including privacy, algorithmic bias, and equitable access, must be managed to promote responsible adoption. The chapter concludes that teleophthalmology, empowered by AI, marks a key step toward scalable, affordable, and patient-centered global eye care.