Landslide hazard of 2017 in Rangamati district had devastating impacts on development, thereby making landslide susceptibility mapping a prerequisite for disaster risk management. This study aims to map the future landslide susceptible areas by overlaying the landslide inventory of 2017 with causative factor maps using WoE and MFR and compare their results to determine that statistical model describes the susceptibility of the landslide occurrence better than the other. The analysis shows that although both models define the spatial relationship of past landslides with the triggering factors in a same way but in case of mapping, MFR had overestimated the high and low susceptible areas and underestimated the moderate susceptible areas than WoE. When validated from success rate curve by plotting the percentage of landslide susceptibility index rank against the percentage of cumulative landslide occurrence, it shows that the WoE model describes the landslides better than the MFR model. About 20% of the high susceptible areas include 85% of the total landslide area in case of the WoE model but the MFR model includes only 20%. On the other hand, the WoE model describes that 30% highly susceptible area covers more than 99% of the total landslide area while MFR defines only 78%.