The burden of newborn illnesses continues to have an effect on the well-being of the people in Nepal, making neonatal death an important public health concern there. In order to predict mortality caused by newborn disorders in Nepal, this study used sophisticated time series analytic techniques, such as the ARIMA model. The research uses several diagnostic tools to guarantee the accuracy of the forecasting model, including the Augmented Dickey-Fuller (ADF) test, Autocorrelation Function (ACF), Partial Autocorrelation Function (PACF), and Box-Jenkins model. This study aims to aid policymakers and healthcare providers in Nepal by shedding light on the evolution of neonatal disorders. This, in turn, will allow for the creation of more effective interventions and better public health outcomes.