Background: Diabetic foot ulcers (DFUs) are a major complication of diabetes mellitus and a leading cause of non-traumatic lower limb amputations worldwide. Accurate risk stratification is essential to guide treatment and prevent limb loss. The Wound, Ischemia, and foot Infection (WIfI) classification system developed by the Society for Vascular Surgery integrates three critical components influencing diabetic foot outcomes. This study aimed to estimate the sensitivity of the WIfI scoring system in predicting amputation among patients with diabetic foot ulcers in a tertiary healthcare setting. Methods: A prospective observational study was conducted among 115 patients presenting with diabetic foot ulcers at the Department of General Surgery, Government Medical College, Thiruvananthapuram. Participants meeting inclusion criteria were recruited consecutively. WIfI scoring was performed at presentation based on wound characteristics, ischemia (using ankle–brachial pressure index), and infection severity. Patients were followed for six months to determine outcomes, including the need for amputation. Data were analysed using SPSS version 27. Sensitivity, specificity, and receiver operating characteristic (ROC) curve analysis were performed. Results: The mean age of participants was 61.1 ± 8.7 years, with males comprising 65.2% of the sample. Overall, 65.2% of patients underwent some form of amputation. Higher grades of ischemia and infection were significantly associated with increased amputation risk (p < 0.01). Among patients with WIfI stage ≥3, 63 out of 64 required amputation compared to 12 among those with stage <3. The WIfI system demonstrated a sensitivity of 84% and specificity of 97.5% in predicting amputation. ROC analysis showed excellent predictive ability with an area under the curve of 0.924 (95% CI: 0.869–0.979). Conclusion: The WIfI classification system is an effective and reliable tool for predicting amputation risk in patients with diabetic foot ulcers, facilitating early risk stratification and improved clinical decision-making.