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As population and water demand increase, accurate assessment of water resources is imperative for sustainable development. This study aims to develop a map of the potential groundwater zone for the northwestern part of the Gulf of Suez. A hydrographical basin of the study area covers approximately 1007 km 2 . A geographic information technique (GIS) with remote sensing (RS) dataset was used in a quantitative assessment approach for groundwater resource evaluation. This study applies a GIS-based model integrated with remote sensing data for groundwater potential zone mapping due to the industrial and touristic development in the area. The thematic layers used are allocated to scores and weights using a linear equation approach. High scores and weights are assigned to the higher controlling class of groundwater. However, the groundwater availability varies spatially and temporally depending upon various controlling factors. For this purpose, six groundwater occurrences and controlling factors, including elevation, slope, lineaments, curvature, lithological units, and stream network, were mapped. The most reliable outcome of this paper is that with a digital elevation model, slope, curvature, lithological units, lineaments, and stream network thematic layers, it is possible to develop a reliable groundwater potentiality zones map. The quaternary deposits and Wadi filling were identified as perfect groundwater potential zones with low elevation and slope, allowing a considerable volume of water and high infiltration rates. The final potential map showed different categories of suitability zones of potentiality in the site. The map of the potential groundwater zone was divided into the traditional five possible categories or classes: very low potentiality, low potentiality, moderate potentiality, high potentiality, and very high potentiality. Furthermore, the very high and high potential zones of groundwater classes represent approximately 38% of the total area. Additionally, two main trends of lineaments are NE-SW and NW-SE. Field data of productive water wells in the present study site were used to validate the model. The data showed that the predicted results were reliable, and the model performed well with the applicability of such an approach in similar areas.