Abstract: Pyrolysis-mass spectrometry (Py-MS) is a powerful analytical technique that combines thermal decomposition of samples with mass spectrometric detection, enabling rapid, high-throughput, and in situ analysis of complex biological materials. This review systematically summarized recent advances in Py-MS and its derivative techniques for the detection and characterization of major biomolecules, including proteins, nucleic acids, and lipids. Three principal pyrolysis configurations, i.e., micro-tube, Curie-point, and laser pyrolysis, were described in detail, highlighting their operational mechanisms, advantages, and suitability for different sample types. A significant technical evolution discussed is the integration of in situ thermally assisted hydrolysis and methylation (in situ THM) using tetramethylammonium hydroxide (TMAH), which enhances the volatility and detectability of non-volatile biomolecules by converting them into methylated derivatives, thereby improving analytical sensitivity and specificity. The application of Py-MS in protein analysis reveals characteristic pyrolysis pathways, such as decarboxylation, deamination, and cyclization, leading to diagnostic products like diketopiperazines (DKPs), which serve as valuable markers for amino acid composition and protein structure inference. For nucleic acids, Py-MS facilitates the identification of nucleobases and methylated derivatives, with TMAH derivatization significantly improving the detection of nitrogenous bases and supporting microbial identification and extraterrestrial biosignature detection, as demonstrated in planetary missions such as Mars Curiosity and ExoMars. In lipid analysis, Py-MS enables rapid profiling of fatty acid methyl esters (FAMEs) from whole cells, allowing for Gram-type differentiation and pathogen identification without extensive sample preparation. The technique has also been successfully applied to specialized targets such as bacterial spores via dipicolinic acid detection, and bioplastics (e.g., polyhydroxyalkanoates), highlighting its versatility. Despite its strengths, Py-MS faces several challenges, including suboptimal transmission efficiency of pyrolysis products to the mass spectrometer, complex spectral interpretation due to overlapping fragmentation pathways, and the lack of standardized pyrolysis spectral libraries. Moreover, current systems often lack portability and require rapid vacuum stabilization for field applications. Future developments should focus on miniaturizing MS instrumentation, integrating multidimensional separation techniques (e.g., ion mobility spectrometry), and applying artificial intelligence for automated spectral interpretation and biomarker identification. With continued innovation in these areas, Py-MS is poised to transition from a laboratory-based tool to a robust platform for real-time, in-field analysis in clinical diagnostics, environmental monitoring, biosecurity, and industrial biotechnology.