Although the modifications of the aging face have been widely described, to our knowledge, there are no studies that quantitatively analyze the degree of soft tissues facial ptosis. Using a specific iPhone application, the faces of a heterogeneous group of volunteers were scanned and studied with the aim to virtually measure the entity of facial ptosis.Two facial scans, upright and supine, were performed by using the Bellus3D Face app for iPhone in a sample of 60 volunteers. We virtually superimposed the two scans, and then, we calculated the discrepancy between them through the Geomagic Design X 3D software. A multivariate regression statistical model was used to analyze the correlation between the mean discrepancy values compared to three main variables: age, BMI and gender. Mean ptosis increases with age (coeff. = 0.02; 95% CI = 0.01-0.02, p < 0.001), BMI (coeff. = 0.03; 95% CI = 0.01-0.05; p < 0.001) and has been found higher in females (female versus male: coeff. = 0.22; 95% CI = 0.13-0.31; p < 0.001). The method we used allowed us to measure the degree of ptosis, and to make a complete morphological study of the effect of gravity on the facial surface in a very accurate, low cost and easily reproducible way.