Rapid urbanization and unplanned land development have transformed Dhaka into one of the most densely built metropolitan areas in South Asia, leading to increased surface heat accumulation and energy consumption within the built environment. Numerous studies have reported a progressive rise in Dhaka’s Land Surface Temperature (LST), ranging between 19 °C and 31 °C during the pre-monsoon months, accompanied by a strong negative correlation between the Normalized Difference Vegetation Index (NDVI) and LST, and a positive correlation between the Normalized Difference Built-Up Index (NDBI) and LST. This indicates that decreasing vegetation and expanding impervious surfaces are major contributors to the city’s thermal inefficiency. The present study aims to assess energy efficiency patterns in the urban landscape of Dhaka by integrating remote sensing, GIS, and data-driven modeling techniques. Landsat 9 imagery and VIIRS nighttime light data were processed to derive NDVI, NDBI, and LST layers, while building footprints and road networks were extracted from OpenStreetMap to represent urban form. A supervised Random Forest model was employed to estimate the relative importance (weights) of these variables in influencing surface temperature distribution. Spatial overlay analysis and correlation assessment revealed that areas with high built-up intensity and low vegetation cover exhibit significantly higher surface temperatures, implying lower energy efficiency. In contrast, green and peri-urban zones demonstrate lower LST values, reflecting enhanced cooling potential. The resulting energy-efficiency map delineates critical urban heat zones that require mitigation through landscape-based interventions. This research underscores the importance of urban greening, reflective roofing, and compact yet sustainable vertical development as strategies to reduce thermal stress and improve energy performance. This study contributes to evidence-based urban planning approaches that can guide policymakers in designing more climate-resilient and energy-efficient cities in Bangladesh.