The objective of this study was to determine the optimal meniscal radiomic features to classify people who will develop an incident destabilizing medial meniscal tear. We used magnetic resonance (MR) images from an existing case-control study that includes images from the first 4 years of the Osteoarthritis Initiative (OAI). For this exploratory analysis (n = 215), we limited our study sample to people with (1) intact menisci at the OAI baseline visit, (2) 4-year meniscal status data, and (3) complete meniscal data from each region of interest. Incident destabilizing meniscal tear was defined as progressing from an intact meniscus to a destabilizing tear by the 48-month visit using intermediate-weighted fat-suppressed MR images. One reader manually segmented each participant's anterior and posterior horn of the medial menisci at the OAI baseline visit. Next, 61 different radiomic features were extracted from each medial meniscus horn. We performed a classification and regression tree (CART) analysis to determine the classification rules and important variables that predict incident destabilizing meniscal tear. The CART correctly classified 24 of the 34 cases and 172 out of 181 controls with a sensitivity of 70.6% and a specificity of 95.0%. The CART identified large zone high gray level emphasis (i.e., more coarse texture) from the posterior horn as the most important variable to classify who would develop an incident destabilizing medial meniscal tear. The use of radiomic features provides sensitive and quantitative measures of meniscal alterations, allowing us to intervene and prevent destabilizing meniscal tears.