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<p> Many settlements in the Guatemala City Metropolitan Area (GCMA) face significant possibilities of fatalities due to their location in steep ravines that are subjected to periodic large-scale landslides. Since the housing in the at-risk areas is relatively low-cost, it is typically cost-prohibitive to mitigate the risk to an acceptable level. Thus, permanent relocation is the only truly viable option to ensure the long-term safety of everyone. However, there are several economic and social obstacles impeding successful implementation of a relocation program. Still, there are many other landslide risk reduction techniques (such as retaining walls, community drainage systems, and alert systems) implemented by government organizations and non-profit groups. These techniques are helpful in landslide risk reduction (LRR), but residents are only partially involved in the entire process. Therefore, increasing residents&rsquo; education and ability to better understand their level of landslide risk will help with LRR. Residents can integrate and collaborate with the government organizations and non-profits implementing mitigation techniques and of even greater benefits, the education and ability for residents to understand their landslide risk can provide additional avenues for LRR not otherwise achievable. The purpose of this research is to develop a landslide-risk-rating-system (LRRS) that can be used by trained residents to better understand their risk (similar to other landslide or rockfall hazard-rating systems commonly used by department of transportation organizations). The focus of this LRRS is only on small-scale landslides (typically the size of a house or less) because evaluating the risk of large-scale landslides is too complicated to be done by trained non-technical experts. The LRRS asks questions related to landslide risk that can be used to calculate a landslide risk score to indicate the relative level of risk. The LRRS was created by reviewing published literature documenting other landslide rating systems and incorporating similar factors correlated with landslide risk. Then, forty sites were visited in the GCMA to inventory the factors at houses that are vulnerable to landslides in order to evaluate which factors were most useful for predicting the relative risk. The predicted risk scores were compared to ranked risk scores estimated by the author to ensure the results were valid. Statistical analysis identified which of these factors best-predicted landslide risk. These factors include slope angle, slope height, strength of slope material or material type, aperture of cracks, spatial impact, largest probable landslide volume, largest probable percentage of the living area that could be impacted from a landslide, and total person-hours a living area is occupied per day. Future work should focus on the transformation of the tool into a more user-friendly format for use by residents, the implementation process, and monitoring plan. </p>