Aims. Prognostic thresholds to identify new type 2 diabetes mellitus (T2DM) cases using the HOMA-IR have not been defined. We studied the HOMA-IR performance to identify incident T2DM cases and to assess if the thresholds varied according to urbanization and altitude in Peru. Methods. Longitudinal analysis. The outcome was incident T2DM cases: self-report diagnosis and fasting glucose. The exposure was the HOMA-IR. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC) was estimated with 95% confidence intervals (95% CIs). Results are presented overall and stratified by study site (Lima, Tumbes, urban Puno, and rural Puno), rurality (urban, semiurban, and rural), and altitude (low and high). Results. A total of 3120 participants (mean age: 55.6 years, 51.2% females) contributed data to this analysis. The median baseline HOMA-IR was 1.7 (IQR 1.0–2.9), with median values ranging from 1.1 in rural Puno to 2.0 in Lima and Tumbes (p < 0 001). Overall for incident T2DM, the AUC was 0.69 (95% CI: 0.64–0.74) with an empirical threshold of 2.8 yielding a positive likelihood ratio of 2.30 and a negative one of 0.61; the positive and negative predictive values were 14.6% and 95.7%, respectively. The empirical thresholds varied within the variables of interest, for example, from 0.9 in urban Puno to 2.9 in Lima. Conclusions. Using the HOMA-IR to identify incident T2DM cases seems to yield moderate accuracy. The HOMA-IR could help improve identifying people at high risk of T2DM.