This paper aims to delve deeply into the practical guidelines for the application of artificial intelligence(AI)in the diagnosis of anterior ocular diseases in ophthalmology. Given the complexities and variability inherent in the images associated with the research of anterior segment diseases, AI has traditionally found its principal application in the sphere of posterior segment diseases within ophthalmology. However, with the evolution and advancement of AI technologies, notably machine learning and deep learning, alongside an exponential surge in anterior segment electronic image data, the implementation of AI in the domain of corneal, conjunctival, lens, and eyelid disease is not only feasible but has become a reality. The Ophthalmic Imaging and Intelligent Medicine Branch of the Chinese Medical Education Association, in tandem with the Ophthalmology Professional Committee of the International Translational Medicine Association, have orchestrated a consortium of experts. These specialists have synthesized the most recent progressions, both nationally and internationally, in the application of AI in the diagnosis of anterior ocular diseases. This includes its use in corneal, conjunctival, lens, and eyelid diseases, and provides an analysis of the current challenges faced as well as the future directions of development. This guideline has been formulated through several iterations of thoughtful discussion and revisions. Its purpose is to empower clinical ophthalmologists with a reliable framework to facilitate the enhanced application of AI in diagnostic decision-making and clinical research for anterior ocular diseases.