<h3>Study Objective</h3> To evaluate the predictive value of individual symptoms in the pathologic diagnosis of endometriosis and to create a predictive model for the presence of endometriosis in symptomatic patients. <h3>Design</h3> Retrospective review of patients who underwent surgical evaluation for possible endometriosis between 10/2018 and 12/2020. Statistical association between symptoms and histopathologic diagnosis of endometriosis was calculated using Fisher's exact test. An Elastic-Net logistic regression model was created to predict presence of endometriosis based on preoperative symptoms. <h3>Setting</h3> Clinical sites within a multi-state U.S. academic hospital system. <h3>Patients or Participants</h3> Female patients, >18 years old, with symptoms concerning for endometriosis, who underwent laparoscopy and biopsy. <h3>Interventions</h3> None. <h3>Measurements and Main Results</h3> A total of 499 patients were reviewed and 325 patients were confirmed to have histopathologic presence of endometriosis. Symptoms of pelvic pain (82.2%, p<0.05), dysmenorrhea (71.0%, p<0.05), dyspareunia (38.5%, p<0.05), deep dyspareunia (54.4%, p<0.05), dyschezia (17.5%, p<0.05), diarrhea (12.6%, p<0.05), dysuria (11.7%, p<0.05), and heavy menstrual bleeding (46.8%, p<0.05) all demonstrated a significant association with a pathologic diagnosis of endometriosis. Normal and underweight BMI (51.2%, 3.3%) were also associated with endometriosis (p<0.05). Patient age, as well as symptoms of hematochezia, constipation, urinary frequency, urinary urgency, and hematuria did not demonstrate a significant association. Patients previously diagnosed with endometriosis (29.5%, p<0.05) or interstitial cystitis (5.2%, p<0.05) were associated with pathologic diagnosis of endometriosis. Previous diagnoses of adenomyosis or myofascial pain syndrome were not significantly associated with endometriosis. Out-of-sample bootstrapping using our predictive model resulted in an AUC = 0.765 (95% CI = 0.703 - 0.822), sensitivity = 0.888 (95% CI = 0.813 - 0.955), and specificity = 0.503 (95% CI = 0.339 - 0.631) to predict the presence of disease. <h3>Conclusion</h3> An effective model to accurately predict the presence of endometriosis in patients prior to surgery was created based on self-reported symptoms, age, and BMI. Future research is needed to validate this model.