In light of the gradual depletion of fossil fuels and emerging environmental concerns, there is a hot topic to make use of lignocellulosic biomass to produce biobased value-added fuels, chemicals, and materials worldwide. However, bioconversion is normally hindered by the complex structure and heterogeneous components (cellulose, hemicelluloses, lignin and pectin) distribution in the cell wall assembly. Therefore, to overcome the recalcitrance, biomass pretreatment became an essential step towards low-cost biomass conversion. In this process, it is greatly importance to have a comprehensive understanding of the chemical composition, structural characteristics of cell walls and their deconstruction mechanism in biomass conversion for efficient utilization of agroforestry biomass. Raman spectroscopy has been used to investigate the structure of cell walls at a multi-scale due to its simple sample preparation, high sensitivity, and quantitative and qualitative analysis of the characteristics of samples in situ. Moreover, the chemical structure of the main components of cell walls and micro-zone distribution information can be provided by Raman spectroscopy combined with microtechnique to realize the dynamic change of composition of visualization research. Firstly, it introduces the working principle of Raman spectroscopy. On account that cellulose, hemicellulose and lignin have different Raman characteristic signals. The concentration and distribution of different components in a certain region can be calculated by integrating the characteristic Raman bands. Secondly, the research progress of Raman spectroscopy application in the field of biomass conversion was summarized. It is especially reviewed that the analysis methods for revealing the spatial distribution pattern and migration regularity of main components within cell walls during dilute acid, hydrothermal and alkali pretreatment processes. It provides an effective way to explore the dynamic dissolution mechanism of cell wall components induced by biomass pretreatments at cellular and subcellular levels. In addition, to solve the problems of excessive number of collected spectra and difficult analysis, this work mainly introduces two Raman data analysis methods, namely principal component clustering analysis and vertex component analysis, which are used to extract characteristic information and perform spectral classification, so as to further explore the spatial distribution and molecular structure of specific components. Finally, based on the above analysis, we also discuss the future challenges and prospects of Raman spectroscopy in the field of biomass conversion, which will provide technical reference for related research.