Kidney disease, the ninth leading cause of death in the United States, has one of the poorest diagnostic efficiencies of only 10% 1 . Conventional diagnostic methods often rely on light microscopy analysis of 2D fixed tissue sections with limited molecular insight compared to omics studies. Targeting multiple features in a biopsy using molecular or chemical reagents can enhance molecular phenotyping but are limited by overlap of their spatial and chromatic properties, variations in quality of the products, limited multimodal nature and need additional tissue processing. To overcome these limitations and increase the breadth of molecular information available from tissue without an impact on routine diagnostic workup, we implemented label-free imaging modalities including stimulated Raman scattering (SRS) microscopy, second harmonic generation (SHG), and two photon fluorescence (TPF) into a single microscopy setup. We visualized and identified morphological, structural, lipidomic, and metabolic biomarkers of control and diabetic human kidney biopsy samples in 2D and 3D at a subcellular resolution. The label-free biomarkers, including collagen fiber morphology, mesangial-glomerular fractional volume, lipid saturation, redox status, and relative lipid and protein concentrations in the form of Stimulated Raman Histology (SRH), illustrate distinct features in kidney disease tissues not previously appreciated. The same tissue section can be used for routine diagnostic work up thus enhancing the power of cliniopathological insights obtainable without compromising already limited tissue. The additional multimodal biomarkers and metrics are broadly applicable and deepen our understanding of the progression of kidney diseases by integrating lipidomic, fibrotic, and metabolic data.