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Sea surface temperature (SST) is a critical parameter in understanding the dynamics of oceanic and atmospheric systems and predicting future climate trends. In this study, we use data obtained from the European Space Agency Climate Change Initiative, specifically from the Sea Surface Temperature Climate Change Initiative (SST CCI) project, to model SST in the Zonguldak and Bartın provinces using the autoregressive integrated moving average (ARIMA) method. The dataset covers 40 years from 1981 to 2022 (longitude 31.25 and latitude 40.95) and includes an assessment of FMS trends and seasonal variations. The results show a slight but consistent increase in SST over the study period, with a mean squared error of 0.07.The changing SST trends in the Zonguldak and Bartın provinces have important implications for several industries and sectors, including fisheries and tourism. The results of this study can help inform decision- making in these areas as well as policy decisions pertaining to climate change adaptation and mitigation strategies. Our findings also provide valuable insights into the effectiveness of the ARIMA methodfor modeling SST data and the potential limitations of the data obtained from the SST CCI project. [ABSTRACT FROM AUTHOR]