Although total hip arthroplasty (THA) has been established as a cost-effective intervention, some patients experience ongoing pain and dissatisfaction. There is interest in predicting postoperative outcomes based on preoperative data, but the relative contribution of different preoperative factors is unclear. The study's aim was to develop multivariable prediction models for the assessment of patient-reported outcomes. Registry data on 1412 patients undergoing THA for osteoarthritis at two hospitals between 2013 and 2018 was used. Potential predictors included age, sex, body mass index, spoken language, education level, previous THA, American Society of Anaesthesiologists (ASA) score, lower back pain, depression/anxiety, other lower limb arthritis, number of other comorbidities, the preoperative expectation of pain and function, EuroQol Visual Analogue Scale (EQ-VAS) and preoperative OHS. Radiographic scores were also used: joint space narrowing (JSN), osteophytes, sclerosis, and an overall grade based on the Kellgren-Lawrence (KL) classification. Outcomes assessed were the patient-rated improvement, satisfaction, and OHS at six months. JSN or overall KL scores were the most important predictors (P < .001) for all outcomes, with better radiographic scores associated with worse outcomes. Other predictors associated with poorer outcomes were lower back pain and lower expectation (predicting poor improvement), lower education and higher ASA (predicting lower satisfaction) and younger age, female sex, non-English speakers, lower preoperative EQ-VAS, lower education, back pain, and anxiety/depression (predicting lower OHS). Preoperative radiological scores are an important predictor of patient-reported outcomes at six months postoperatively. Understanding the relative strengths and significance of different factors in predicting outcomes will help the clinician and patient decision-making for THA.