The present study focused in identifying and monitoring land use/land cover changes of the Bamenda mountain forest (North West region of Cameroon) using remote sensing data from 1978 to 2010 and GIS technology. To begin with, the massive change observed on the study site was largely attributed anthropogenic factors rather than natural disturbances. to keep going, it was deemed necessary that determining the magnitude of change of the Bamenda mountain chain forest could be effective and important to understand the rate of the changes. Moreover, Mapping, evaluating and predicting the trends of major land use/land cover changes of this site could be possible and useful. The methodological approach adopted for the research work was an interdisciplinary approach technique which combined the qualitative research technique from a social science perspective with a remote sensing and GIS technique from a geographical perspective. The remote sensing data-set used for the research work was cloud free and of the dry season, downloaded and classified in support of ground control points and google earth images. reconnaissance information gathered from the field of study was also analyzed in support of the issue being investigated. To better understand this, land sat MSS, TM and ETM+ for the years 1978, 1988 and 2010 respectively were used. A false color composition using bands 5, 4 and 3 was performed on the images to identify the different LULC types of the study area. These images were later on classified using the NDVI analysis for the identification of the changes in land cover and land use types. The NDVI results obtained were reclassified with the help of a supervised classification technique using maximum likelihood algorithm where the main land use and land cover categories were identified and mapped to understand the trends of the changes that occurred during the studied dates. The research revealed a significant loss of the vegetation cover of the Bamenda Mountain, which was the focus of interest of the study. According to the research findings, from 1978 to 1988, bare rocks, built-up, cultivated lands and savannah all increased at the detriment of the forest that dropped to 48.68% covering a surface area of -4520.49km2. Likewise from 1988 to 2010, both the forest and savannah dropped to 1.32% and 19.23% covering surface areas of -7046km2 and -1026.56km2 respectively. This thus showed the usefulness of remote sensing and GIS in pairing up less recent images to more recent ones in examining and demonstrating changes for a vast ecosystem and for a long period of time. This necessitated some proposed solutions such as employment of competent forest guards, reforestation and afforestation, and even improving technologies to combat the rate of forest degradation of this site which is under risk of invasion.