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Simple Summary: Tumor recurrence is a relatively common event in papillary thyroid cancer (PTC). The aim of this study was to analyze the time-varying pattern of recurrence in PTC using annual hazard function and establish a predictive model for early and late recurrences. We found a double-peaked pattern of annual hazard of recurrence, with the risk being highest during the first 5 years after surgery. We also found distinct clinico-pathological parameters that could independently predict the occurrence of early recurrence (first 5 years) as compared to late recurrence (after 5 years). Overall, this study highlights the importance of long-term follow-up of PTC patients. Furthermore, the findings of our study could help in establishing individualized treatment and surveillance plans in PTC patients. Predicting the pattern of recurrence in papillary thyroid cancer (PTC) is necessary to establish optimal surveillance and treatment strategies. We analyzed changes in hazard rate (HR) for tumor recurrence over time in 1201 unselected Middle Eastern PTC patients. The changes in risk were further analyzed according to clinical variables predictive of early (≤5 years) and late (>5 years) recurrence using Cox regression analysis to identify patient populations that remain at risk. Tumor recurrence was noted in 18.4% (221/1201) patients. The annualized hazard of PTC recurrence was highest during the first 5 years (2.8%), peaking between 1 and 2 years (3.7%), with a second smaller peak between 13 and 14 years (3.2%). Patients receiving radioactive iodine (RAI) therapy had lower recurrence hazard compared to those who did not (1.5% vs. 2.7%, p = 0.0001). Importantly, this difference was significant even in intermediate-risk PTC patients (0.7% vs. 2.3%; p = 0.0001). Interestingly, patients aged ≥55 years and having lymph node metastasis were at persistent risk for late recurrence. In conclusion, we confirmed the validity of the double-peaked time-varying pattern for recurrence risk in Middle Eastern PTC patients and our findings could help in formulating individualized treatment and surveillance plans. [ABSTRACT FROM AUTHOR]