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Self-murder is a global public health concern with profound societal and individual impacts. This exploration paper aims to dissect self-murder rates from colorful perspectives and develop prophetic models to understand and potentially alleviate this critical issue. We employ a multidisciplinary approach, exercising data analysis, machine literacy, and socio- profitable factors to gain perceptivity into the factors impacting self-murder rates and produce prophetic models that can help in forestallment sweats. The study covers an expansive dataset gauging several times and multiple countries to give a comprehensive view of this complex problem