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Abstract Assessing trends in population abundance and demographics is crucial for managing long‐lived and slow‐reproducing species. Obtaining demographic data, and age‐structure information, is challenging, notably for cetaceans. To address this, we combined Unoccupied Aerial System (UAS; drone) photogrammetry data with long‐term (>20 years) photo identification data to assess the age‐structure of the critically endangered sub‐population of common bottlenose dolphins (Tursiops truncatus) of the Gulf of Ambracia, Greece. We compared our findings with two extensively studied non‐endangered bottlenose dolphin populations (T. aduncusin Shark Bay, Australia, andT. truncatusin Sarasota Bay, USA). Using a log‐linear model, we estimated the total body lengths (TL) of 160 known‐aged dolphins between 2021 and 2023 from blowhole‐to‐dorsal‐fin distance (BHDF) measurements collected during surfacing. Subsequently, we tested four growth models to establish an age‐length growth curve. We assessed the sub‐population's age‐structure using three methods: (1) UAS‐derived TL estimates, (2) age‐length growth curve and (3) long‐term monitoring data (i.e. actual age‐structure). UAS‐measured TL (247.6 ± 32.2 cm) and UAS‐estimated TL (246.0 ± 34.7 cm) of the Greek sub‐population showed no differences. The Richards Growth model suggested an asymptotic length of 258.5 cm. In Greece, resulting age‐structure estimates across the three methods revealed no significant differences (P > 0.1). The Gulf of Ambracia and Shark Bay populations shared similar age‐structures, while Sarasota had higher proportions of 2–10 year‐olds and lower proportions of 10+ year‐olds. All populations had a comparable proportion of 0–2 year‐olds (~14%), indicating a similar reproductive rate. Our findings suggest stability in the Greek sub‐population; however, additional monitoring of reproductive parameters is essential before concluding its status. We demonstrated the effectiveness of UAS‐photogrammetry in rapidly quantifying population age‐structure, including scenarios with limited or no demographic data. This technique shows promise for enhancing precision, timeliness, cost‐effectiveness and efficiency in population monitoring and informing timely conservation management decisions.