Abstarct: In recent years, determining the rate of shoreline changes by the historical trend method has been of great interest to researchers and has been repeatedly reported as a basis for predicting future changes. Among the outstanding achievements of this research (using numerical modelings, field studies, etc. to reduce model errors) to provide a frxamework that expresses the relationship between water level and the rate of shoreline changes in the study area and through it can predict future changes in the shoreline, taking into account the general conditions of the region as well as the water level at the projected time horizon. For this purpose, about 22 km of shorelines of one of the sensitive areas with high economic value areas in Mazandaran province was selected for the study, which is adjacent to the commercial port of Fereydoonkenar and has seen a wide range of human interventions during periods of increasing and decreasing water level. The Digital Shoreline Analysis System (DSAS) plays a role in this research as a historical trend method. baxsed on the Caspian Sea water level data, two incremental and decremental scenarios were selected for modeling. The results of the endpoint rate and the linear regression rates and the weighted linear regression rates approaches of the digital shoreline analysis model were obtained as the shoreline change rate for both scenarios. It was observed that the progress and reversal of the shoreline of the study area were directly dependent on the water level, and the graphical and statistical comparisons of the results of the prediction of the shoreline changes indicated the appropriate accuracy for most areas. Finally, using the results of this frxamework, the action was taken to predict the shoreline in a specific time position in the future. With this in mind, let us show how the model’s achievements can be used to predict the future of the shoreline.