This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies focus on evaluating the probabilities of occurrence of different landslide types with certain characteristics. They describe methods for determining the spatial distribution of landslide intensity, characterizing elements at risk, assessing potential damage, quantifying vulnerability, and performing quantitative risk analysis. The paper is intended for use by scientists, engineers, geologists, and other landslide experts. Despite improvements in understanding landslide mechanisms and mitigation techniques, landslides still cause significant deaths and economic losses globally. Recent studies show that landslide-related deaths are concentrated in less developed countries due to limited resources for hazard and risk understanding. Cooperative research and capacity-building are needed to support local and regional administrations in landslide risk management. Authorities and decision-makers need maps showing areas at risk from landslides to inform development plans and implement risk mitigation measures. Various methods for assessing landslide susceptibility, hazard, and risk are available, with guidelines proposed by institutions to standardize terminology and data needed for mapping. However, methodologies vary significantly between countries. To manage risk, it must be analyzed and evaluated. Landslide risk for an object or area is calculated based on a time frame for which the expected frequency or probability of an event exceeding a minimum intensity is evaluated. Quantitative risk analysis (QRA) is distinguished by input data, procedures, and final risk output. QRA quantifies the probability of a given level of loss and associated uncertainties. QRA is important for scientists and engineers as it allows objective and reproducible risk quantification, enabling comparisons between locations. It also helps identify gaps in input data and weaknesses in analyses. For landslide risk managers, QRA allows cost-benefit analysis and prioritization of management actions. For society, QRA increases awareness of risk levels and the effectiveness of actions. QRA requires accurate geological and geomechanical input data and high-quality DEMs to evaluate scenarios, design events, and return periods. Lee and Jones (2004) warned that landslide probability and adverse consequences are estimates, and numbers may conceal significant errors. QRA is not necessarily more objective than qualitative estimations, as probability may be based on personal judgment. However, it facilitates communication between geoscience professionals, landowners, and decision-makers. Risk for a single landslide scenario can be expressed as R = P(Mi)P(Xj|Mi)P(T|Xj)VijC, where R is the risk due to a landslide of magnitude Mi on an element at risk located at distance X from the landslide source. The three basic components of Eq. 1 are hazard, exposure of elements at risk, and their vulnerability. These are characterized by spatial and nonspatial attributes. The goal of these recommendations is to present an overview of existing methodologies for quantitative analysis and zoning of landslide susceptibility, hazard, and risk atThis paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies focus on evaluating the probabilities of occurrence of different landslide types with certain characteristics. They describe methods for determining the spatial distribution of landslide intensity, characterizing elements at risk, assessing potential damage, quantifying vulnerability, and performing quantitative risk analysis. The paper is intended for use by scientists, engineers, geologists, and other landslide experts. Despite improvements in understanding landslide mechanisms and mitigation techniques, landslides still cause significant deaths and economic losses globally. Recent studies show that landslide-related deaths are concentrated in less developed countries due to limited resources for hazard and risk understanding. Cooperative research and capacity-building are needed to support local and regional administrations in landslide risk management. Authorities and decision-makers need maps showing areas at risk from landslides to inform development plans and implement risk mitigation measures. Various methods for assessing landslide susceptibility, hazard, and risk are available, with guidelines proposed by institutions to standardize terminology and data needed for mapping. However, methodologies vary significantly between countries. To manage risk, it must be analyzed and evaluated. Landslide risk for an object or area is calculated based on a time frame for which the expected frequency or probability of an event exceeding a minimum intensity is evaluated. Quantitative risk analysis (QRA) is distinguished by input data, procedures, and final risk output. QRA quantifies the probability of a given level of loss and associated uncertainties. QRA is important for scientists and engineers as it allows objective and reproducible risk quantification, enabling comparisons between locations. It also helps identify gaps in input data and weaknesses in analyses. For landslide risk managers, QRA allows cost-benefit analysis and prioritization of management actions. For society, QRA increases awareness of risk levels and the effectiveness of actions. QRA requires accurate geological and geomechanical input data and high-quality DEMs to evaluate scenarios, design events, and return periods. Lee and Jones (2004) warned that landslide probability and adverse consequences are estimates, and numbers may conceal significant errors. QRA is not necessarily more objective than qualitative estimations, as probability may be based on personal judgment. However, it facilitates communication between geoscience professionals, landowners, and decision-makers. Risk for a single landslide scenario can be expressed as R = P(Mi)P(Xj|Mi)P(T|Xj)VijC, where R is the risk due to a landslide of magnitude Mi on an element at risk located at distance X from the landslide source. The three basic components of Eq. 1 are hazard, exposure of elements at risk, and their vulnerability. These are characterized by spatial and nonspatial attributes. The goal of these recommendations is to present an overview of existing methodologies for quantitative analysis and zoning of landslide susceptibility, hazard, and risk at