Forests provide critical ecological, cultural, and economic services but are increasingly threatened by deforestation, climate change, and anthropogenic pressures. Monitoring forest ecosystem integrity is crucial for addressing these challenges. This systematic review employs the PRISMA framework to evaluate current methodologies for assessing forest health, analyzing 13 studies from an initial dataset of over 75,000 articles. The review examines the strengths and limitations of traditional field-based approaches and advanced technologies such as remote sensing, machine learning, and GIS tools. Traditional methods offer detailed site-specific insights, whereas advanced tools provide broader spatial and temporal coverage but lack standardized frameworks and consistent data integration. Key findings highlight the need for clear definitions of forest health, standardized indicators, and improved integration of monitoring approaches across ecosystems. Identified research gaps include limited applications of tools like LiDAR and hyperspectral imaging and insufficient cross-ecosystem comparisons. This study recommends refining methodologies and fostering scalable, robust monitoring systems to support sustainable forest management worldwide.