Plastic pollution remains one of the world’s most prevalent pollution problems, especially in the Philippines. The main objective of the study is to develop a methodology for locating marine litter accumulations between remote sensing images and a particle-tracking model beyond the sparse historical information and sources of Manila Bay Pasig River Outfall’s plastic litter from 2017 to 2019. We aim to bridge the gap between the two technologies by using the earliest classified marine litter points as input sources for the particle-tracking model, then comparing other detections with the calculated positions from the model and a control simulation of marine litter particles from Pasig River's mouth. Marine litter was detected near coastal areas and in open waters, with 68% average accuracy. With a localized hydrodynamic model, the particle tracking model successfully simulated 188 remotely sensed plastic particles in both input approaches from 2017 to 2019. Marine litter positions showed higher correlation when using remote sensing sources as opposed to the riverine source of Pasig River, with average R-squared values from 0.91 and 0.92 to 0.95 and 0.96, respectively, in each axis; however, both approaches also showed high variance. In all results, we observed significant accumulation near the Manila Bay Port, particularly during the wet season. In summary, our study showed significant advantages in using remote sensing data in conjunction with particle tracking models in locating marine litter with high spatial and temporal resolution, and highly recommends coupling the technologies together for future studies.