Spatial multi-omics involves the analysis of biomolecules such as proteome, metabolome, and lipidome within their native spatial context in tissues or cells. This approach provides a comprehensive understanding of biomolecular networks in specific biological environments. Mass spectrometry imaging (MSI) has emerged as a powerful technique for mapping the region-specific molecular distribution in regions of interest (ROIs) with its high spatial resolution. Laser capture microdissection-based mass spectrometry (LCM-MS) is another well-established workflow for spatial multi-omics, allowing the reliable characterization of biomolecules in ROIs with the high sensitivity. To advance the current analytical application, we introduce matrix-assisted laser desorption/ionization (MALDI)-MSI-guided LCM-MS approach that integrates MALDI-MSI metabolomics with LCM sample-based LC-MS/MS metabolomics and proteomics. As a proof of concept, we applied this approach to mouse brain tissue. MALDI-MSI identified over 300 putative metabolites and lipids, with high abundance of PE (36:0), PC (38:4), and PG (38:4) in the hippocampus and PI (36:4), PE (38:6), and docosahexaenoic acid in the cortex regions, respectively. Both hippocampus and cortex regions were isolated as two ROIs using LCM, followed by LC-MS/MS-based metabolomics, lipidomics and proteomics. LCM-metabolomics annotated 186 compounds encompassing small molecules and lipids. Several molecules revealed the distinct molecular abundance between the two regions. Importantly, acetylcholine (ACh), acetyl-L-carnitine (ALCAR), inosine, and nicotinamide exhibited noticeable up-regulation in the hippocampus, consistent with previous reports. LCM-proteomics identified over 3,500 proteins across the two ROI regions, with 796 differentially expressed proteins (DEPs). Of these, 498 and 298 proteins showed significantly more abundant in the cortex and hippocampus regions, respectively. Biological network analysis using DEPs highlighted that their molecular pathway and phenotype showed strongly aligned with region-specific characteristic. Our MALDI-MSI-guided LCM-MS approach enables comprehensive profiling and quantitative analysis of proteome, metabolome, and lipidome, providing valuable insights into complex biological systems and spatial molecular distribution.