Assessing sea level rise (SLR) due to global warming is of great interest to coastal populations, such as those along the Gulf of Mexico (GOM), due to increased tidal flooding and storm surges. Global mean temperature is expected to increase over 3°C by 2100 due to anthropogenic-induced greenhouse gas emissions that lead to increased sea level by melting of ice sheets and associated ice shelves and glaciers. In addition to melting of ice masses, SLR by thermal expansion due to predicted rise in global mean temperature contributes to a rise in global mean sea level (GMSL). Vertical land movement (VLM) is a significant factor in relative sea level (RSL) change. The gradual collapse of the forebulge of the Laurentide Ice Sheet contributes to subsidence through glacial isostatic adjustment, while depression of the lithosphere due to sediment loading from major rivers also contributes to the sinking land surface. Compaction of Holocene sediments in the northern GOM is another factor in the VLM of the region, while hydrocarbon and groundwater extraction also contribute to subsidence along the Texas and Louisiana coasts. Probabilistic projections based on representative concentration pathways, autoregressive integrated moving average (ARIMA) forecasts based on tide gauge data, and lowess smoothing of global SLR data from satellite altimetry have been used in prior studies to assess RSL rise. The objective of this study is to analyze the methods of forecasting RSL for their usefulness in planning and risk assessment for communities along the northern GOM. Preliminary results suggest that ARIMA modeling is most useful for short-term RSL forecasting while probabilistic projections provide a greater range of possible RSL rise scenarios useful in planning. This research adds to the body of work on RSL and focuses on providing locally-significant projections, with relative uncertainties, of RSL rise in both the short and long-term. Assessing the localized effects of RSL rise demonstrates that RSL rise rates in communities along the Texas and Louisiana Gulf coasts exceed the global average and this knowledge is imperative to coastal communities’ preparedness planning. Therefore, RSL rise projections into the future should be used to test plans and policies against different scenarios with low to high probability of occurring.