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Along with the continuous renewal of computer technology, artificial intelligence (AI) has been widely and gradually applied in the medical field of medicine.Research concerning machine learning and deep learning for making ophthalmological diagnosis is expanding.As glaucoma is an irreversible, blinding disease, early diagnosis and treatment are extremely important for improving patients’ prognosis.Currently, AI is mainly combined with several auxiliary examinations (fundus photography, visual field tests, optical coherence tomography, etc.) to diagnose and treat glaucoma.AI models are built to segment, classify, and predict the results of image examinations, which is helpful for making diagnoses and predicting glaucoma progression.With the development of algorithms and technologies, the accuracy, sensitivity, and specificity of diagnosis gradually improve.Diagnosing and treating glaucoma require comprehensive consideration of multiple auxiliary examination results, so screening high-quality data and developing more systematic and comprehensive AI models remain to be explored.Currently, only several AI models are associated with glaucoma in the anterior examinations, so it is possible to begin studying the machine and deep learning models associated with ultrasonic biological microscopy and anterior segment optical coherence tomography.This paper, therefore, reviews the application of AI in glaucoma diagnosis.