<![CDATA[Background: In vitro fertilization (IVF) remains one of the most effective assisted reproductive technologies for the management of infertility; however, its success rate varies widely across populations and clinical settings. In Indonesia, data-driven evaluations of IVF success predictors remain limited, and locally validated prognostic tools to support individualized counseling and treatment planning are scarce. This study aimed to identify factors associated with successful pregnancy outcomes among couples undergoing IVF at the WIN Infertility Clinic, Puri Bunda Hospital, Denpasar. Methods: A retrospective cohort study with a case–control approach was conducted using secondary data from medical records of 243 infertile couples who underwent IVF cycles between January 2023 and December 2024. Clinical pregnancy confirmed by laboratory and ultrasound findings was classified as the success group (n = 100), while unsuccessful cycles constituted the control group (n = 143). Variables evaluated included female age, basal hormonal profile, ovulation induction protocol, number of embryos transferred, body mass index (BMI), infertility duration, and infertility status. Univariate and multivariate logistic regression analyses were performed to identify independent predictors, followed by the development of a predictive scoring model. Results: The overall clinical pregnancy rate was 41.2%. Multivariate analysis demonstrated that four variables were independently associated with IVF success: female age (adjusted OR [aOR] 0.91; 95% CI 0.85–0.98; p = 0.012), number of embryos transferred (aOR 1.68; 95% CI 1.22–2.33; p = 0.001), normal BMI (aOR 2.00; 95% CI 1.12–3.59; p = 0.019), and duration of infertility (aOR 0.92; 95% CI 0.86–0.99; p = 0.041). A predictive scoring system derived from these factors demonstrated moderate discriminatory performance (AUC = 0.724). Conclusion: Female age, number of embryos transferred, BMI, and infertility duration are significant independent predictors of IVF success at this center. The proposed scoring model may serve as a practical tool to support individualized patient counseling and optimize treatment planning in IVF programs.]]>
