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Many rivers suffer acutely from various pollutants that pose risks to plant and animal life, the environment, and human health due to the lack of regulations to protect the rivers’ water quality and environmental safety. Weight Quality index method (WAQIM) based on 12 water quality parameters (Mg, Cl, EC, TDS, Ca, PO4, SO4, TH, Na, Turbidity, TSS, and Temp) using (SPSS) program Artificial Neural Network (ANN) methods. The water quality index results for AL-Atshan River were greater than 100, classified as poor and polluted water, compared to AL-Rumaitha River, which showed less than 100 pollution for most of the study period, classified as more suitable and needing less treatment than AL-Atshan River. The neural network obtained a mathematical model that can predict the total dissolved solids of AL-Atshan and Al-Rumaitha rivers with very high accuracy, as the determination coefficients were 96% and 98%, respectively, and the sampling results support this analysis, indicating that AL- Atshan River has a salinity higher than World Health Organization Standard limits. (EC was about 3000μs/cm TDS about 1600 ppm), while Al-Rumaitha’s results were within WHO specification limits (EC about 1500 μs/cm, TDS about 800 ppm).