The aim of this Diploma Thesis is the development of a mathematical model for the estimation of cy-cling routes in the city of Athens, utilizing high-resolution data. More specifically, it aims to identify the critical factors that influence the cycling trips carried out in the areas of Chalandri and Vrilissia, utilizing crowdsourced data from the “Strava Metro” platform. Provided that these data were captured spatially through a Geographic Information System, they were enriched with additional spatial data that related to both road and traffic conditions in the examined road network and multiple land uses in its surround-ing area. Afterwards, three log-normal regression mathematical models were developed with the ulte-rior purpose of estimating the annual cycling trips conducted on each road section in the areas of Cha-landri and Vrilissia, but also in both areas combined. The result of this process is the demonstration of the positive effect of the average speed of cycling on the number of cycling trips, while the vast majority of cycling trips carried out on primary, secondary and tertiary road network of the areas that are under investigation. In conclusion, the most critical influencing factors on cycling trips concern road infrastruc-ture and traffic conditions on each road section, such as the average speed of cycling trips, the category of road section and its length. Additionally, it is noteworthy that cycling trips are significantly influenced by the proximity of the cycling route to infrastructure for facilitating cyclists, such as bicycle parking and public transport stops.