Purpose: The purpose of this study was to develop a probabilistic estimation of the strength of risk factors associated with early dental implant failure and rank them by importance. Materials and Methods: A systematic literature search was performed on PubMed, Web of Knowledge, Scopus, Cochrane Central Register of Controlled Trials, and grey literature up to April 2017. A total of 368 records were identified. Following the removal of duplicate and irrelevant records, 56 were screened. Eight studies met the inclusion criteria, in which seven statistically significant risk factors for early failure were selected and used to build a conceptual simulation model. Selected risk factors were, namely, "male sex," "smoking," "bone quality," "short implants," "wide implants," "adjacent teeth," and "periodontitis." Monte Carlo simulation with 100,000 iterations and a sensitivity analysis were performed to evaluate the risk estimates of these risk factors and to identify which of the risk factors are more important in influencing the model, respectively. Results: The performed simulation model has shown a significant difference in terms of estimated effects of the risk factors on early failure rate. As a result, the most sensitive risk factor was found to be "periodontitis" with the second being "adjacent teeth" and the third "smoking." The least sensitive factor for early failure was "wide implants." Conclusion: This study develops a better understanding of the importance of risk factors for early dental implant failure by an estimated ranking. Schlagwörter: dental implants, Monte Carlo method, risk factors, treatment failure