The study entails detecting forest degradation and modeling future scenario using GIS and remote sensing, in Elgeyo/Marakwet County, a case study of Embobut forest, it is evident that forests have been managed for several years in the world, but in most cases especially in the developing world, various regimes have tried to come up with institutional to guide forest management with no much success, in many countries, there is no regular monitoring system that collects information about the situation of the forests and trends of the distribution. This makes it difficult to quantify the status of the existing forest cover. We used high-resolution satellite imagery as well as GIS and remote sensing software (ArcGIS and ENVI) with mathematical models to project the forest status, apart from satellite images there will be a ground truthing using Global positioning system (GPS) as data collection tool to as well as use of Auxiliary data; which will include Socioeconomic and data for the years 1980, 1990, 2000 and 2010. Policy implications especially with the enactment of Kenya forest act, 2005 was examined. recorded positive changes hence increased in size while all other forest classes decreased in size. The study found out that the total forest loss was 7,172.31 hectares, this represents a loss of 28 percent of the total forested area that existed in 1986 which corresponds to an annual forest loss of 286.892 hectares. According to this study, as population increased the rate of deforestation also increased. The future scenarios from the studies were based on a fixed annual deforestation rate and a conclusion is made that Bare land & rocky and water bodies classes increased in area while Mixed Podocarpus latifolius, Juniperus-Nuxia-Podocarpus factus, Tree ferns Cyathea manniana & Bamboo, Acacia abyssica & Scrubby grassland classes decreased in size. As Population grew forestry loss increased, between 1986 and 2011, the total forest loss was 7,172.31 hectares. Future Scenario found that with the same trend, there will be no forest remaining natural forest block by the year 2038 in the study area.