This chapter looks at the use of a Markov chain–cellular automata method to model and then predict land-use change in Dhaka. Initially land-use/land-cover maps for three separate time periods were derived from satellite images and evaluated against ground truth. The Markov chain method was then used to establish transition probability matrices between land-cover categories for the time periods represented. The use of cellular automata in this work enables neighbourhood interactions to be accounted for. After an initial calibration run, the combined method is then used to predict land use and land cover in 2022 and 2033.