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Purpose: To evaluate the classification performance of a new method to individualize reference ranges for biomarkers of muscle recovery in elite handball. Methods: In a longitudinal observational study, creatine kinase (CK) and urea levels were assessed in 16 male elite handball players during the 2019–20 preseason. Blood samples were collected at prespecified time points when players were considered either recovered or nonrecovered. Initially, linear mixed-effects models were calculated, as outlined in the study design, to examine the effect of recovery status on CK and urea levels. Finally, a fixed-effect model was calculated for urea based on the law of parsimony. Individualized reference ranges were calculated using a recently published algorithm. To investigate whether the individualized approach resulted in a more accurate classification of recovery status (recovered or nonrecovered), it was compared with a group-based approach derived from the same data set, utilizing predefined error rates. Results: Linear mixed-effects models showed a large effect of recovery status on CK (P d = 3.49) and a small effect on urea (P = .018, d = 0.382). In contrast to CK (P = .017), urea had no significant interindividual variation. Hence, individualization was examined only for CK. The numerical decrease in both CK error rates by the individualized approach was significant for the test-pass error rate (P = .0196, ϕ = .19). Conclusions: Our findings underscore the critical role of CK for monitoring in team sports such as handball. The observed improvement in CK error rates suggests a promising opportunity to individualize biochemical monitoring, although further studies encompassing larger sample sizes are warranted.