Mechanical thrombectomy (MT) is crucial for improving functional outcomes for acute ischemic stroke. Length of stay (LOS) is a reimbursement metric implemented to incentivize value-based care. Our study aims to identify predictors of LOS in patients undergoing MT at a high-volume center in the United States. This was a retrospective study of patients who underwent MT at a single institution from 2017 to 2023. Patients who experienced mortality during their course of hospital stay were excluded from this study. Extended LOS (eLOS) was defined as the upper quartile (≥75th) of the median duration of hospital stay. Univariate and multivariate analyses were performed, with P values < .05 denoting statistical significance. Seven hundred three patients met criteria for inclusion. The median age of the cohort was 72 years (IQR: 61-82), and 57.2% was female. The median LOS was 6, IQR: 4-10. A total of 28.9% of the cohort (n = 203) patients experienced eLOS. The multivariate regression model identified age (odds ratio [OR]: 0.98, 95% CI: 0.97-0.99), diabetes mellitus (OR: 1.68, 95% CI: 1.15-2.44), and hemorrhagic transformation of stroke (OR: 2.89, 95% CI: 0.39-0.90) as predictors of eLOS, whereas antiplatelet use before admission (OR: 0.55, 95% CI: 0.34-0.89) and higher baseline modified Rankin Scale before stroke were associated with lower odds (OR: 0.59 [0.39-0.90]; P < .05) of eLOS. By identifying predictors of eLOS, we provide a foundation for targeted interventions aimed at optimizing post-thrombectomy care pathways and improving patient outcomes. The implications of our study extend beyond clinical practice, offering insights into healthcare resource utilization, reimbursement strategies, and value-based care initiatives.