Objectives: 1. Compare how old we look to others, as a measure of facial ageing, with the presence of health conditions and links to longevity. 2. Investigate if A.I. predictions of age are equivalent to human predictions of age. Introduction: How old we look for others has long look been thought as an indicator of how well we are ageing compared to others of the same age. Indeed, age estimations of how old individuals look in facial photographs (perceived facial age) have been demonstrated to be reproducible when the average age is taken from groups of assessors. In addition, those who look old for their age have greater wrinkling, age spots etc highlighting that these average age estimations are a good overall measure of facial ageing features. Hence, perceived facial age can be used to investigate facial ageing links to health. Materials / method: We measured perceived facial age in an observation study design of 2679 men and women aged 51.5–87.8 years of European descent, and investigated whether looking young for one’s age was associated with less disease and age-related conditions. Next, we investigated whether perceived age was predictive of mortality 12 years from when the photographs were taken in a study of 1826 twins aged over 70 years. Finally, we went back to the observational study and used A.I. to estimate perceived facial age and tested whether these ages were also associated with the same age-related conditions. Results: We found looking young for one’s age was associated with less osteoporosis, less chronic obstructive pulmonary disease, less age-related hearing loss and fewer cataracts, and with better global cognitive functioning. Supporting evidence was found for such links with osteoporosis and cognition. In the twins study, we found that looking young for one’s age was predictive of longevity in 12 years of follow-up data, and these links were due to changes in facial appearance. Finally, we found that A.I. age estimations of perceived facial age gave very similar associations as human estimated age. Conclusion: Strong evidence was found for associations between facial ageing and heath, as well as longevity 12 years into the future. Associations between A.I. predictions of age and health were similar to those from human age estimations, which opens-up easier routes to measure facial ageing in human health studies and further understand why facial appearance is an indicator longevity and health.