<p>Endometriosis is a chronic inflammatory condition that affects an estimated 1 in 10 women but is often mis- and underdiagnosed due to its non-specific symptoms and the lack of a non-invasive diagnostic test. This study aimed to identify and validate a potential non-invasive biomarker for endometriosis. This study applied quantitative proteomics discovery approaches to identify and validate non-invasive biomarkers of endometriosis with a long-term goal of leveraging them for purposes of diagnosis and therapeutic monitoring. Isobaric tags for relative and absolute quantification (iTRAQ) combined with mass spectrometry were used to identify and quantitate proteins and peptides in urine samples from participants with surgically-confirmed endometriosis (<i>n</i> = 73) and 1:1 age-matched participants never diagnosed with endometriosis (<i>n</i> = 73). Among those aged 25–47 at urine collection, Epidermal Growth Factor (EGF) (validated using monospecific enzyme-linked immunosorbent assays (ELISA)) was present at significantly lower levels in the urine of participants with surgically-confirmed endometriosis compared to controls (<i>P</i> = 0.02) and had an excellent negative predictive value (NPV) of 94.3% with a cutoff of &gt; 800 pg/ug as determined by Bayes’ formula. Urinary EGF levels were also significantly lower in the urine of participants aged 25–47 with endometriosis who experience acyclic pelvic pain compared to samples from age-matched controls who did not report acyclic pelvic pain (<i>P</i> = 0.007) such that the presence of acyclic pelvic pain increased the NPV of EGF to 96.8% as determined by Bayes’ formula. These data demonstrate that urinary EGF has potential as a novel, non-invasive, accurate and objective biomarker for endometriosis diagnosis and prognosis of this disease.</p>