ABSTRACT Geographic information systems (GIS) along with remote sensing (RS) techniques have enhanced our understanding of the surrounding environment. Land changes that took place in the past or that might happen in the future affect almost every aspect of our environment, economy, and decision making processes. Therefore GIS and RS are used to simulate, or predict land changes for different variety of recipients. Studying land changes can be beneficial whether to individuals, organizations, decision makers, stakeholders, and eventually to the entire society to ensure making correct decisions. The selection of the most suitable land change model for a given application is crucial. One of the main objectives of this study is to compare two land change models that are considered commonly used and both belong to the same land change modeling approach. In the comparison three main aspects were focused on; first how each model handle the calibration process that is concerned with the selection of proper explanatory variables and how the model connect those variables with resulting changes in a similar manner to previous observed changes for the same study area. The second comparison aspect i¬s concerned with the simulation part of the modeling process. Simulation deals with how a model allocates changes and simulates spatial patterns by using predefined explanatory variables. The third and final aspect focuses on how each model performs assessment of the resulting simulated spatial patterns since the credibility of each model depends on how accurate its results. The two land change models were compared to assess land cover changes in Al-Sharqiya governorate, Egypt. Using Landsat images acquired in 1984, 2000, and 2017, the study compared how each model simulated changes using two images between 1984 and 2000, and to identify the accuracy of how each model can predict land cover changes, the 2017 image was used.