Some patients experience severe pain following root canal therapy (RCT) despite advancements in care. We sought to identify factors, which can be measured preoperatively, that predict this negative outcome so that future research may focus on preemptive steps to reduce postoperative pain intensity. Sixty-two practitioners (46 general dentists and 16 endodontists) who are members of the National Dental Practice-Based Research Network enrolled patients receiving RCT for this prospective observational study. Baseline data collected from patients and dentists were obtained before treatment. Severe postoperative pain was defined based on a rating of >/=7 on a scale from 0 (no pain) to 10 (pain as bad as can be) for the worst pain intensity experienced during the preceding week, and this was collected 1 wk after treatment. Multiple logistic regression analyses were used to develop and validate the model. A total of 708 patients were enrolled during a 6-m period. Pain intensity data were collected 1 wk postoperatively from 652 patients (92.1%), with 19.5% (n = 127) reporting severe pain. In multivariable modeling, baseline factors predicting severe postoperative pain included current pain intensity (odds ratio [OR], 1.15; 95% confidence interval [CI], 1.07 to 1.25; P = 0.0003), number of days in the past week that the subject was kept from their usual activities due to pain (OR, 1.32; 95% CI, 1.13 to 1.55; P = 0.0005), pain made worse by stress (OR, 2.55; 95% CI, 1.22 to 5.35; P = 0.0130), and a diagnosis of symptomatic apical periodontitis (OR, 1.63; 95% CI, 1.01 to 2.64; P = 0.0452). Among the factors that did not contribute to predicting severe postoperative pain were the dentist's specialty training, the patient's age and sex, the type of tooth, the presence of swelling, or other pulpal and apical endodontic diagnoses. Factors measured preoperatively were found to predict severe postoperative pain following RCT. Practitioners could use this information to better inform patients about RCT outcomes and possibly use different treatment strategies to manage their patients (Clinicaltrials.gov NCT01201681).