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An Oil Spill Modeling Tool (OSMT) has been developed in this study to predict the transport and fate of oil spills resulting from surface releases. Particularly, the Kullback-Leibler (KL) divergence method is adopted as a performance metric for the first time to formulate a calibration framework for spill trajectory prediction (STP) from the Lagrangian transport model (LTM). By finding the candidate with minimal KL divergences from modeling scenarios using designed parameter combinations, the prediction discrepancy between simulated trajectories of the LTM and oil slicks detected from satellite images is reduced. The developed approach has been evaluated through a comparison analysis between OSMT and Operational Oil Modeling Environment (GNOME) model. Subsequently, a real case study is conducted to examine the applicability and effectiveness of the OSMT. The study results indicate that OSMT can provide reliable spill trajectory simulations, and the KL divergence-based calibration method is effective in calibrating the oil spill LTM.