As the global climate is changing, our focus was on Sea Level Rising (SLR) which is the most threatening phenomenon in this era. Hence to hit the nail on the head, the alteration of surface level for both Global Mean Sea Level (GMSL) and Bay of Bengal (BOB) has been predicted using time series analysis (TSA). Since the time series analysis has some components, those components were brought out from data set and by using these components some terms have been calculated to match with real data. By doing that, training part was constructed and set up a method to predict the results for next years. An endeavor has been done to test the prediction results with a known data set as well as the computation was carried out in order to forecast for unknown data. In this work, the prediction has been done with respect to seasonal effects so that result can be accurate with seasonal variation. With extensive data set, other inconsistency has been considered easily. Mathematical enumeration has added a dynamism with this forecasting thoughtlessly. This study can be used to raise up a wariness among people. Besides this, this research can be used as a grounding for further study.