Coastal aquifer in Muan, Jeonnam, has experienced heavy seawater intrusion caused by the extraction of a substantialamount of groundwater for the agricultural purpose throughout the year. It was observed that groundwater level droppedbelow sea level due to heavy pumping during a dry season, which could accelerate seawater intrusion. Therefore, waterlevel needs to be monitored and managed to prevent further seawater intrusion. The purpose of this study is to develop theautoregressive-cross-regressive (ARCR) models that can predict the present or future groundwater level using its ownprevious values and pumping events. The ARCR model with pumping and water level data of the proceeding five hours(i.e., the model order of five) predicted groundwater level better than that of the model orders of ten and twenty. This wascontrary to expectation that higher orders do increase the coefficient of determination (R2) as a measure of the model''sgoodness. It was found that the ARCR model with order five was found to make a good prediction of next 48 hourgroundwater levels after the start of pumping with R2 higher than 0.9.