Many studies have unveiled the importance of variation in residential property values overtime, but failed to cover different types of residential property value and location. The aim of this research is therefore to model residential property rental value in Bida from 2015 to 2020 with the aid of Geographic Information System (GIS). The study focused on the rental values of the residential property and rental value variation across space. Data collected for this paper includes residential rental values and geographic coordinates from 196 residential properties in the study area, comprising 101 one-bedroom, 80 two-bedroom and 15 three-bedroom apartments. Inverse Distance Weighted (IDW) interpolation tool of ArcGIS was employed in analysing the data. It was found out that the core areas of the town commands lower rental values while the southern part of the town commands higher rental values. It was also found out that one bedroom apartment is the most dominant residential rental property followed by the two bedroom apartments and three bedroom apartments respectively. Geospatial database was produced for each model in a bid to ascertain the level of changes with time. The benefits associated with the application of GIS technology were established by this research and recommends its application to other property values modelling.