Analyzing vulnerability to climate change involves understanding how different systems, communities, and ecosystems are susceptible to the adverse effects of climate variability and extreme weather events. Vulnerability assessment is a crucial component of climate change research because it informs adaptation strategies, risk management, and policy planning. It is generally approached by examining exposure, sensitivity, and adaptive capacity. Exposure refers to the extent to which a system is subject to climate hazards, sensitivity is the degree to which the system is affected by these hazards, and adaptive capacity is the ability of the system to adjust or cope with changes. Several methods have been developed to evaluate these dimensions, combining quantitative, qualitative, and participatory approaches. One of the most widely used methods is the indicator-based assessment. This approach involves the identification of key indicators that reflect exposure, sensitivity, and adaptive capacity. Indicators can include climatic variables such as temperature rise, frequency of extreme weather events, rainfall variability, and sea-level rise, as well as socio-economic indicators like income level, education, health infrastructure, and access to resources. The data for these indicators are typically gathered from national statistics, remote sensing, field surveys, and climate models. These indicators are then aggregated using weighting and scoring methods to produce a vulnerability index. This index helps to compare vulnerability across regions or communities, prioritize areas for intervention, and monitor changes over time. Another method is model-based assessment, which uses simulation models to predict the impacts of climate change and evaluate vulnerability. Models such as General Circulation Models (GCMs), Regional Climate Models (RCMs), and integrated assessment models provide projections of future climate conditions. These projections can be combined with ecological or socio-economic models to understand potential impacts on agriculture, water resources, human health, and infrastructure. For example, hydrological models can simulate how changing precipitation patterns will affect river flows and flood risks, while crop models can estimate yield reductions under different temperature and precipitation scenarios. Model-based assessments are particularly valuable for long-term planning because they allow scenario analysis, helping policymakers explore different adaptation strategies under uncertain future conditions. Participatory methods have become increasingly important in vulnerability assessment because they incorporate local knowledge and context-specific