There are many different time series forecasting models available today, and each one needs the correct data pretreatment and analysis to produce a useful prediction. The purpose of this report is to conduct a comparative analysis of the most popular Time Series estimators in order to highlight the growing interestin time series forecasting techniques. Time series data are being produced in a variety of fields more and more. It supports the growth of time series research and provides data for the study of time series analysis methods. This study makes an effort to classify and cover the current modelling approaches for time seriesdata. Additionally, we contrast variousapproaches and providea list of futurepossibilities for time series forecasting.