Based on the latest statistics, the number of villages decreased by (18%) of the total number of villages between 1982 and 2019, which indicates an urgent need for a plan to develop the rural settlements in Iraq for spatial balance with the urban area, and the most important challenges and risks that facing this process are the mechanism and criteria for selecting a (mother) village that is a candidate for development with the current situation, to serve the optimum number of inhabitants in a group of neighbouring villages and building modern villages. The overall and main objective of this research was to select potential areas suitable for villages that will be candidates for rural development in Maysan Province south of Iraq by using geographic information system (GIS) methods and remote sensing (RS) techniques. The main data used for this study were Sentinel-2 satellite images with a spatial resolution of 10m; a digital elevation model (DEM) with 12.5m spatial resolution, a topographical map of the study area, the layer of village locations in rural areas, with the data of all these villages included in the comprehensive survey of villages in the Maysan Province. Population, agriculture activity, infrastructure, public services, economic projects, natural characteristics, and site properties, for rural regions are defined as important criteria for identifying sites of select villages for rural development. So, all the thematic layers are assigned weightage depending on importance and priority. Then all the layers are integrated into (The suitability Modeler) one layer by one to produce suitable village sites and demarcated as mother villages candidates for rural development in the study area. The final suitability map for villages of the study area was prepared on ArcGIS Pro 2.8 program and labelled as very high, high, moderate, low, and very low suitable regions out, of the total villages, 52 villages (9.2%) lie in 13 sub-districts (called Nahia), on the middle-south-west parts, along the rivers in Maysan Province, was very high suitable to the candidate for rural development.