Purpose: High cardiorespiratory capacity is a key determinant of human performance and life expectancy; however, the underlying mechanisms are not fully understood. The objective of this pilot study was to investigate biochemical signatures of endurance-performance athletes using high-resolution nontargeted metabolomics. Methods: Elite long-distance runners with similar training and anthropometrical records were studied. After athletes’ maximal oxygen consumption ($\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$) was measured, they were divided into 2 groups: low $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ (<65 mL·kg⁻¹·min⁻¹, n = 7) and high $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ (>75 mL·kg⁻¹·min⁻¹, n = 7). Plasma was collected under basal conditions after 12 hours of fasting and after a maximal exercise test (nonfasted) and analyzed by high-resolution LC–MS. Multivariate and univariate statistics were applied. Results: A total of 167 compounds were putatively identified with an LC–MS-based metabolomics pipeline. Partial least-squares discriminant analysis showed a clear separation between groups. Significant variations in metabolites highlighted group differences in diverse metabolic pathways, including lipids, vitamins, amino acids, purine, histidine, xenobiotics, and others, either under basal condition or after the maximal exercise test. Conclusions: Taken together, the metabolic alterations revealed in the study affect cellular energy use and availability, oxidative stress management, muscle damage, central nervous system signaling metabolites, nutrients, and compound bioavailability, providing new insights into metabolic alterations associated with exercise and cardiorespiratory fitness levels in trained athletes.