As we get older, we experience a progressive loss of visual function in our eyes. Changes in the structures of the ocular tissues, specifically the cornea, lens, retina, retinal pigment epithelium (RPE), choroid, and optic nerve, are the root cause of age-related macular degeneration, which leads to a loss of vision. Aging is linked to a wide variety of eye conditions, including Fuch's dystrophy, dry eye syndrome, cataracts, presbyopia, age-related macular degeneration (AMD), diabetic retinopathy, and glaucoma, amongst others. Vision can be impaired as a result of these conditions in between 4 and 20 percent of people over the age of 65. The term "metabolic syndrome" (MetS) refers to a cluster of cardiometabolic components, some of which include abdominal obesity, hypertension, elevated glucose levels, and dyslipidemia. These components are highly predictive of type 2 diabetes mellitus and cardiovascular diseases (CVD), which eventually cause morbidity and mortality. The retinal age difference has proven itself as an innovative and reliable screening technique for metabolic syndrome and inflammation. When compared to earlier screening methods that were based on blood tests or anthropometric measurements, the retinal age gap is calculated using a deep learning model that automatically integrates all of the information from fundus images. This reduces the likelihood of making an error during manual assessment and eliminates the requirement for invasive testing. We discovered that there was a strong association between MetS and age gaps in the retina, as well as inflammation.