X-ray fluorescence (XRF) is a powerful, non-destructive analytical technique widely used in various fields including environmental science for the elemental analysis. In this chapter, we explore the application of XRF for analysing vegetation tissues. Vegetation analysis is crucial for understanding nutrient dynamics, pollution levels, and overall plant health, making accurate and efficient analytical methods essential. The chemometric tools, such as principal component analysis and partial least squares regression, were to enhance the interpretation of the complex data generated by X-ray fluorescence. These multivariate statistical methods allow for the extraction of meaningful patterns and relationships from the large datasets typically produced in XRF analysis. By integrating XRF with chemometric techniques, we can better differentiate between various plant species, identify stress indicators, and monitor environmental changes reflected in vegetation tissues. This method holds significant potential for applications in environmental monitoring, agricultural management, and ecological research, where understanding the elemental makeup of plants is crucial. Future studies will focus on refining these techniques to improve sensitivity and expand the range of detectable elements, ultimately contributing to more comprehensive environmental assessments.