Over Earth’s 4.54 billion-year history, natural disasters have reshaped its topography countless times. Earthquakes, storms, floods, and droughts are among the most destructive and unpredictable natural disasters. However, satellite data combined with machine learning algorithms now offer new ways to detect early warning signs of these disasters and mitigate their effects. By leveraging Geographic Information System (GIS) data, NASA’s Global Precipitation Measurement (GPM), and other satellite technologies, researchers can analyze massive geospatial datasets to identify subtle patterns imperceptible to humans. This paper explores the role of machine learning and satellite data in predicting natural disasters. It highlights the technological advancements that could significantly reduce the human and environmental toll of these events.