​Under right-hand traffic conditions, Pedestrians significantly affect vehicle right-turn capacity, as right-turn vehicle movements typically interact with opposing pedestrian flows. Despite substantial efforts over several decades to account for this effect in right-turn capacity models, current models may lack scalability when addressing multiple possible scenarios. In this study, a general model of the effect of pedestrians on right-turn capacity is developed by theoretically deriving the unblocked time for vehicles during the green phase. The proposed model considers variables such as pedestrian volumes and signal timings, as in several existing models, but also incorporates additional factors, including: 1) the length of the conflict zone, 2) the length and width of the crosswalk, 3) pedestrian types and their respective speeds, and 4) the types of right-turning vehicle. The model is validated under realistic conditions that take into account, for instance: 1) changes in right-turn policies, 2) unbalanced pedestrian volumes by direction, 3) mixed pedestrian traffic, and 4) mixed traffic conditions, along with signal timing and geometric variables as addressed in previous research, through comparisons with a microsimulation. Additionally, comprehensive evaluations are performed by comparing field measurements. Given its ability to account for a wider range of variables, the proposed model is more adaptable to diverse contexts than existing models. Furthermore, these characteristics make the model applicable in future autonomous vehicle environments.