Check dams generally consist of a vertical barrier constructed on ditches, small streams, channels and gullies that have often been formed by the erosive activity of water. A check dam serves many purposes, such as reducing runoff velocity, reducing erosive activities, reducing the original channel gradient, improving bed sediment moisture in adjoining areas, sediment retention and allowing for percolation to recharge aquifers. A check dam interferes with flows in the upstream and downstream channels and dissipates the energy of flowing water. Therefore, identifying the quantitative variables that influence the volume of these structures is crucial for accurately estimating construction costs and their effectiveness. This study aimed to model check dam volumes across 100 sub-basins in eight provinces of Iran (Alborz, East Azerbaijan, Ilam, Bushehr, Qazvin, Fars, Mazandaran, and Hamadan). The database for modeling included 27 environmental features from each of the 100 sub-basins, and Gene Expression Programming (GEP) was used for the modeling process. The results indicated that the key features for estimating check dam volume among the 27 variables studied are precipitation, slope, drainage density, TWI index, shape factor, elevation difference, concentration time and NDVI index. The evaluation of the modeling, based on R², RRMSE, RAE and NSE values, revealed that the most accurate model for Qazvin province had values of 0.97, 0.18, 0.17 and 0.96, respectively. In contrast, the least accurate model for Mazandaran province had values of 0.80, 0.38, 0.35 and 0.80. Additionally, the results demonstrated that environmental characteristics could be used with high accuracy to estimate check dam volumes quickly. This allows for the relevant costs to be estimated before implementing check dams, facilitating the prioritization of areas effectively.