This chapter introduces one of the most critical problems in ophthalmology, specifically the diagnosis and detection of diabetic retinopathy (DR). Developing a fast, accurate, and reliable method for the early detection of DR is of great clinical importance to prevent blindness in patients. For this reason, various methods for early detection of DR have been investigated and used such as a dilated eye examination, tonometry, fluorescein angiography, optical coherence tomography, and ultrawide-field retinal imaging. With the increased popularity of machine learning, researchers have formulated their own algorithms and methods to detect DR with various rates of success. This chapter overviews past and current diagnostic methods that have been developed for DR. In addition, this chapter addresses new methodologies being developed/researched and some challenges that researchers face in developing fast, accurate, and reliable diagnosis.