Chittagong Metropolitan Area (CMA) is highly vulnerable to landslide hazard, with an increasing trend of frequency and damage. The major recent landslide events were related to extreme rainfall intensities having short period of time. All the major landslide events occurred as a much higher rainfall amount compared to the monthly average. Moreover rapid urbanization, increased population density, improper landuse, alterations in the hilly regions by illegally cutting the hills, indiscriminate deforestation and agricultural practices are aggravating the landslide vulnerability in CMA. It is therefore essential to produce the future landslide susceptibility maps for CMA so that appropriate landslide mitigation strategies can be developed to help combat the impacts of climate change. In this research Geographic Information System (GIS) and Remote Sensing (RS) based Weighted Linear Combination (WLC), Logistic Regression (LR) and Multiple Regressions (MR) models were used to scientifically assess the landslide susceptible areas. Later the performances of the models were compared using Relative Operating Characteristic (ROC) method. The area under ROC curves (AUC) is indicating that the WLC_1, WLC_2, WLC_3, LR and MR models had AUC values of 0.839, 0.911, 0.885, 0.767 and 0.967, respectively. The verification results showed satisfactory agreement between the susceptibility maps and the existing data on the 20 landslide locations. In the second stage of this research, soil samples from 17 different landslide vulnerable areas were collected to analyse different properties of soil related to shear strength. It is known as Atterberg Limit/ Soil Consistency Test. Liquid Limit, Flow Index, Plastic Limit, Liquidity Index, Shrinkage Limit; Linear Shrinkage and Plasticity Index parameters were tested in laboratory. In all cases, it is found that the locations are highly vulnerable to landslides. At the end of this research, some recommendations like- understanding the human adaptation to landslide risks, the processes and mechanism of landslides in CMA; developing a Web-GIS based early warning system, implementation of the existing master plan, creating awareness among the local people, increasing cooperation among different public/ private/ autonomous/ NGOs organizations and generating facilities for proper evacuation system in crisis moment etc. were stated. The authors believe that the outcome of this research shall help the endangered local communities, urban planners and engineers to reduce losses caused by the future landslides in CMA by means of prevention, mitigation and avoidance.