In mangrove ecosystems, the significance of litterfall as a key contributor to ecosystem productivity and soil nutrient dynamics is well established. This study conducted a comprehensive analysis of litterfall patterns within a hyper-arid saline mangrove ecosystem in the United Arab Emirates (UAE), revealing substantial monthly fluctuations. The annual litterfall ranged from 0.107 to 0.768 Mg/ha (+/- 0.093 Mg/ha), with the lowest values observed in February and the highest in August. The investigation further examined the relationship between litterfall and ten distinct remotely sensed vegetation indices, utilising multispectral imagery from the Sentinel-2 satellite mission. The findings indicated a weak correlation between litterfall and several vegetation indices. Nevertheless, exemplary predictive performance was achieved through a random forest regression model (RF), yielding an R2 value of 0.81 and a root mean square error (RMSE) of 6.71. The analysis identified the Normalised Difference Moisture Index (NDMI), Plant Senescence Reflectance Index (PSRI) and Transformed Vegetation Index (TVI) as the most significant variables influencing litterfall dynamics. The study underscores the critical importance of comprehending monthly litterfall patterns and leveraging remote sensing methodologies for effectively monitoring and managing mangrove ecosystems amid shifting climatic conditions.