Urine-based proteomic profiling is a novel approach that may result in the discovery of noninvasive biomarkers for diagnosing patients with different diseases, with the aim to ultimately improve clinical outcomes. Given new and emerging analytical technologies and data mining algorithms, the urine peptidome has become a rich resource to uncover naturally occurring peptide biomarkers for both systemic and renal diseases. However, significant analytical hurdles remain in sample collection and storage, experimental design, data analysis, and statistical inference. This study summarizes, focusing on our experiences and perspectives, the progress in addressing these challenges to enable high-throughput urine peptidomics-based biomarker discovery.