The study aimed to determine the existing linear influence levels of various causative factors of Urban Heat Island (UHI) by using Geographically Weighted Regression Model (GWR) that determines non-stationarity by generating a new equation for each sample size. Urban heat island occurs when higher temperatures reside in urban areas compared to surrounding areas due to the replacement of natural vegetation with construction materials during development purposes. Time Series with Linear Regression was used to determine the linearity between dependent and independent variables. Moderate Resolution Imaging Spectroradiometer (MODIS) products such as MOD11A1, MCD43A1, MOD09A1 and MOD13A1 were used to acquire Land Surface Temperature (LST), Albedo, Indexed-Based Built-Up Index (IBI) and Enhanced Vegetation Index (EVI) respectively. In-situ datasets of the wind speed were acquired from Tanzania Meteorological Agency (TMA). UHI was observed to have a non-linear trend with IBI and wind speed and a linear trend with Albedo and EVI. The strongest values of UHI were observed at the city center, IBI was observed as a leading causative factor by having a non-lineality influence of 0.023 followed by Albedo, wind speed and EVI with an influence of 0.019, 0.016 and -0.015 respectively. Since IBI and Albedo contribute more to the development of heat island, urban residents should be encouraged to use construction materials with a lower absorption rate of solar energy.