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This paper introduces a new application in the burgeoning world of computational politics. We use support vector machines (SVM) and back propagation learning algorithm neural network models to forecast American congressional voting outcomes. Our proposed approach effectively associates the views of representatives of the American Congress on specific national topics with their political party membership as republican or democrat, creating an artificially intelligent prediction method of the The result of legislative voting is dependent on prior experience of how congress representatives view national problems. Understanding is derived from actual legislative archives that are unclassified and accessible for academic purposes online. The results obtained The experimental findings indicate that our innovative approach and implementation may be extended to related voting polls in the future. predict the political preferences of party representatives.