Purpose <p>This exploratory pilot study, employing a single-center and cross-sectional design, aimed to characterize urinary protein alterations associated with pediatric metabolic-associated fatty liver disease (MAFLD) and to identify preliminary candidate proteins associated with MAFLD status within a cohort of children with obesity.</p> Methods <p>In this single-center, cross-sectional observational study, urine samples were collected from 39 children and assigned to three groups: healthy controls (<i>n</i> = 10), simple obesity (<i>n</i> = 14), and obesity with MAFLD (diagnosed by ultrasonography, <i>n</i> = 15). Data-independent acquisition (DIA)–based quantitative proteomics was performed. After quality control, shared proteins across groups were analyzed by one-way ANOVA and trend clustering. Functional enrichment was conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Pearson correlation was used to examine associations between key proteins and clinical metabolic indicators. Exploratory discriminatory potential within this cohort was assessed using Receiver operating characteristic (ROC) curves.</p> Results <p>A total of 2,824 intersecting proteins were identified, and 49 showed significant differences among the three groups. Trend analysis and fold-change filtering (|log₂FC| &gt; 0.585) identified 19 core proteins with consistent expression gradients across the healthy, obese, and MAFLD groups. Among these, 6-phosphogluconolactonase (PGLS), dipeptidyl peptidase 7 (DPP7), and complement factor I (CFI) demonstrated notable correlations with liver function markers and glucose–lipid metabolic indices. ROC analysis indicated that PGLS provided the strongest discrimination.</p> Conclusion <p>We performed urinary proteomic profiling to characterize metabolic alterations in pediatric MAFLD. Our analysis identified distinct protein signatures across the HC-OB-MAFLD spectrum, highlighting metabolic dysregulation, oxidative stress, and complement activation as primary features of disease progression. While PGLS, DPP7, and CFI emerged as potential biomarkers, PGLS demonstrated the greatest potential for distinguishing MAFLD from simple obesity in this specific cohort. Due to the small sample size (<i>n</i> = 39) and cross-sectional design, these results provide preliminary molecular insights that require large-scale, longitudinal validation to confirm their clinical utility.</p> Trial registration <p>International Traditional Medicine Clinical Trial Registry ITMCTR2025001222, December 31, 2024. Retrospectively registered.</p>