Introduction Post-thyroidectomy hypocalcemia remains a significant surgical complication with varying reported incidence rates. While traditional focus has centered on surgical factors, the role of metabolic predictors in calcium homeostasis disturbances remains incompletely understood. Methods We conducted a single-center retrospective analysis of 1,760 thyroidectomy patients based on data obtained from King Abdullah International Medical Research Center (KAIMRC), Saudi Arabia, evaluating metabolic predictors and long-term calcium homeostasis patterns. Preoperative assessment included thyroid function tests, glycemic control, vitamin D status, and anthropometric measurements. We have followed the TRIPOD + AI statement which provide updated guidance for reporting clinical prediction models that use regression or machine learning methods, We developed a risk stratification model using multivariate logistic regression and implemented mixed-effects modeling for longitudinal analysis. Recovery patterns were evaluated through standardized follow-up at immediate postoperative, one-month, three-month, six-month, and one-year timepoints. Results Post-thyroidectomy hypocalcemia occurred in 585 patients (33.2%, 95% CI: 31.0-35.4%). Preoperative thyroid stimulating hormone (TSH) levels appeared to be the strongest predictor (OR 2.24, 95% CI 1.71-2.93, p<0.0001), followed by T3 (OR 1.34, 95% CI 1.19-1.51) and glycated hemoglobin (Hemoglobin A1C), (OR 1.18, 95% CI 1.07-1.30). Our risk stratification system, including TSH, vitamin D, and immediate postoperative calcium, achieved superior discrimination (AUC=0.921) and effectively categorized patients into low (6.5%), intermediate (14.6%), and high-risk (83.2%) groups. Recovery patterns revealed a non-linear trajectory, with an unexpected decline at six months (79.71%) before maximal improvement at one year (88.61%). Conclusions Our findings highlight and demonstrate the significant role of metabolic factors in post-thyroidectomy hypocalcemia risk and challenge the current standard recovery assumptions, suggesting the need for extended monitoring protocols and comprehensive metabolic assessment in perioperative management.