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Earthquake prediction is currently the most important task required for probability, hazard, risk mapping, and mitigation. In the past, various traditional and machine learning models have been used for risk assessment. It is unlikely that anyone will ever be able to predict earthquakes accurately, but with advancements in deep learning algorithms, predictions can become more precise and closer to the actual natural disaster. Different machine learning approaches and deep learning models based on radon anomaly detection have been compared, opening the field for further developments.