Earthquake is a natural disaster that can impose enormous amounts of damage and can lead to loss of several lives. Earthquakes are very challenging and one of the most difficult study topics but research on earthquake prediction can save a lot of lives and can also aid in minimizing structural damage to buildings and government losses. The idea of our research is to create a model that predicts earthquake magnitude via machine learning techniques. An earthquake’s magnitude can be determined based on different geographical topology or the number of seismic stations that recorded the event. Regression analysis, a powerful statistical methodology or technique to assess the correlation between 1 or numerous independent variables and dependent variables. This project consists of a comparative analysis of various regression models, like Support Vector Regression (SVR), Linear Regression (LR), and others. The final result will later show whether the regression model is more effective and helpful in estimating the earthquake’s magnitude.