Understanding the relationship between bedload transport and morphological changes is crucial in braided river systems, particularly those on steep slopes. Despite significant research efforts in recent decades, unraveling this interplay remains a complex challenge. Our study delves into this problem, utilizing a physical model to conduct long-duration (500h) experiments of steep-slope braided river systems. To visualize the dynamic changes in the water network, we collected realtime data on bedload transport and captured overhead imagery every ten seconds. By doing so, we could depict the water network's evolution by categorizing different morphological shapes or states based on their similarities, as previous studies have suggested [1,2]. We identified a correlation between sediment transport regimes and the different morphological configurations of our physical model. This correlation allowed us to distinguish distinct bedload transport patterns associated with each morphological state. Building upon this relationship, we developed a probabilistic model based on Markov Chains capable of capturing sudden changes between states, a characteristic of this type of river. Inspired by ideas from previous studies [3,4], this model forecasts alterations in river formations and sediment movement patterns. Our approach enhances the understanding and management of dynamic river systems. It also provides essential information about how sediment transport patterns and river shape interacts, contributing significantly to studying river dynamics and conservation.