RESUMEN
This study employs time series forecasting, specifically Seasonal Auto-Regressive Integrated Moving Average, to predict the radiological impact of uranium mining in Mika, Nigeria. By utilizing meteorological data to model the dispersion of radioactive emissions to receptors, allowing for a comprehensive assessment of potential health and environmental consequences. The study observed a slight change in the Total Effective Dose Equivalent (TEDE) at the nearest residence northeast receptor between the actual and the forecasted data. The findings could be largely because of the basement complex rock formations that characterized the Mika region. The study recommend proper monitoring and evaluation should be done before full-scale mining can be carried out. However, the TEDE is generally below the International Atomic Energy Agency recommended level of 1 mSv per y for public exposure. The research demonstrates the significance of predictive modeling in managing and mitigating the radiological risks associated with uranium mining activities. Findings contribute to informed decision-making and sustainable resource extraction practices in Mika, Nigeria.