Currently available evaluation checklists are developed for specific purposed using different parameters and items determined by different weighting factors. Those items with different weighting are sometimes said that they are based on the engineering judgement and leap of faith and, therefore, there is a limitation to adapt those checklists for slope-stability evaluation in the field. This study reviews factors affecting Rock-slope stability, analyze the relationship between those factors and slope failures using artificial neural network, and proposed a slope-stability evaluation model for adequate weighting for the factors.