Incidence of allergic contact dermatitis (ACD) is rising worldwide as a consequence of raising chemical exposure, especially from biocides present in common water-based products such as cosmetics and household products. Understanding the biological processes involved in skin sensitization is crucial to mitigating ACD. Migration of Langerhans cells to the basal lamina of the skin is a key step in sensitization. Animal testing for sensitization has been largely replaced by alternative in vitro methods due to ethical concerns. This study presents an open-source program using QuPath software enhanced with machine learning to analyze Langerhans cells migration in immunostained human skin samples. We validated scripts for automated detection of skin layers and Langerhans cells position, enabling accurate, reproducible analysis. An ex vivo human skin organo-culture model was used to test Langerhans cells migration after 24-h exposure to four different isothiazolinones diluted in water at different concentrations. The initial results show that the water vehicle has an impact on Langerhans cells migration. We also observed a different Langerhans cells migration pattern for methylisothiazolinone and benzothiazolinone exposed skin compared to octylisothiazolinone. The results suggest that only octylisothiazolinone can induce Langerhans cells migration to the basal lamina of the epidermis as described for sensitizers. This automated approach represents a advancement in ACD risk assessment by minimizing the subjectivity and labor involved in Langerhans cells analysis, providing a valuable tool for future research.