Seismology is crucial for saving as many lives as feasible through earthquake prediction. In order to better analyse and interpret seismic data, a precise and accurate algorithm is required to detect and locate future earthquakes. This paper aims to review the recent papers that have investigated the application of different machine learning (ML) approaches for earthquake forecasts, with the goals of grouping the utilised methods and analysing the major trends in earthquake forecasting and the different seismic indicators used in machine learning algorithm and the performance of the methods were reported. In this regard, we have analysed the different ML Algorithms used in different research paper considered in this paper for estimating magnitude, location, time of earthquakes and recommended an appropriate research approach.

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