This study proposes a prediction method for the identification of areas inside and around cities, that—based on their morphometric and built-up conditions—are prone to develop as hot spots in the highly probable case of cities development. To achieve this objective, hot and cold spots of air temperature distribution for the six largest cities from north-eastern Romania were firstly identified using data from mobile measurements, performed during the warm season. From May to September 2022, 64 mobile measurements were made following a standardized observation plan. The measurements were carried out under calm and stable atmospheric conditions, with clear or partly cloudy skies, before sunrise and immediately after sunset in order to ensure representativeness. Global Moran’s Index was used to assess spatial autocorrelation, while Getis-Ord Gi* was used for hot and cold spot identification. The results describe accurately the built-up ratio and landform morphology conditions of the areas that are warmer (hot spots)/colder (cold spots) than their surroundings. In brief, it can be observed that the occurrence of hot spots is mostly controlled by high imperviousness density values (>45%), while cold spots are shaped mainly by local natural conditions that are favorable for the accumulation of cold air below the thermal inversion band. Secondly, based on the relationship of altitude and built-up ratio with hot spots occurrence, we developed a prediction model of the urban areas that are prone to sustain or evolve into hot spots. The analysis results are meant to serve cities stakeholders involved in the mitigation of the urban heat island effects, helping them to identify the regions that are in risk of becoming excessively warm during future summers.