Identifying individual sea turtles is essential for understanding population dynamics and, in turn, planning conservation efforts. Traditionally, sea turtle individuals are identified through the application of external flipper tags and/or internal passive integrated transponders (PITs). However, sea turtle identification and consequently population studies are hampered by the loss of external flipper tags and migration of PITs. In this study, we assessed the accuracy and time efficiency of the Interactive Individual Identification System software (I3S Pattern v. 4.02) to photo-identify facial patterns of immature captured and free-swimming green turtles Chelonia mydas and hawksbill turtles Eretmochelys imbricata. Using a library of 436 photos representing 189 sea turtle individuals, we evaluated the accuracy and time taken for I3S Pattern to match individuals. A high proportion of individuals were successfully identified from photographs taken of captured turtles (97%) and free-swimming turtles (85%). I3S reduced data analysis time by 80% when compared to the visual assessment of photos, and is further optimised when photographs are of increased quality. These results demonstrate that I3S has great potential to contribute to population studies and management plans by facilitating both specialised research and citizen science programmes.