Osteoarthritis is a common degenerative disorder that affects joints. Despite recent therapeutic advances, osteoarthritis continues to be a challenging health problem, and elderly population is particularly at risk. Pain is the most unbearable symptom experienced by osteoarthritic patients. Currently, several pharmacological medications are available to manage osteoarthritic pain. Opioids, potent analgesics, have shown extraordinary ability to reduce intense pain in many osteoarthritic clinical trials. Although many clinical trials have investigated the efficacy and safety of opioids in osteoarthritic patients, there is an increased need for a study to integrate the reported outcomes and utilize them to achieve a better understanding of efficacy and safety profiles of opioids. Therefore, in our present study, efficacy, safety, and tolerability profiles of opioid compounds used to manage osteoarthritic pain were assessed and compared using a model-based meta-analysis (MBMA). To achieve our goal, a comprehensive database consisting of pain relief compounds with information on summary-level of efficacy over time, adverse events and dropout rates was compiled from multiple sources. MBMA was conducted using nonlinear mixed-effects modeling approach. The results showed that the selected models successfully captured the observed data, and primary efficacy endpoint estimations indicated that the ED50 of oxycodone, oxymorphone, and tramadol were 47, 84, and 247 mg per day, respectively. Efficacy-time course analysis showed that opioids had rapid time to efficacy onset, suggesting potential powerful pain relief effects. Also, it was found that gastrointestinal adverse events were the most opioid-associated and dose-dependent adverse effects. In addition, the analysis revealed that opioids are well-tolerable at low to moderate doses. The results presented here provided clinically meaningful insights into the efficacy and safety of oxycodone, oxymorphone, and tramadol. In addition, the presented framework analysis has a clinical impact on drug development where it can help in optimizing the dose of opioids to manage osteoarthritic pain, making precise key decisions for positioning of new drugs, and designing more efficient clinical trials.