We introduce a semiautomated machine learning method that employs high‐resolution imagery for the species‐level classification of Antarctic pack‐ice seals. By incorporating the spatial distribution of hauled‐out seals on ice into our analytical framework, we significantly enhance the accuracy of species identification. Employing a Random Forest model, we achieved 97.4% accuracy for crabeater seals and 98.0% for Weddell seals....