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Background. There is a growing interest in the application of the capability approach in health economic analysis. The aim of the research reported here is to assess the feasibility of mapping from a condition-specific questionnaire (Western Ontario and McMaster Universities [WOMAC] Osteoarthritis Index) to a capability well-being questionnaire (ICEpop CAPability measure for Older people [ICECAP-O]). Methods. One hundred five osteoarthritis patients requiring joint replacement completed the 5 attributes on the ICECAP-O (attachment, security, role, enjoyment, and control) and the 3 WOMAC categories (pain, stiffness, and physical function). The prediction data set consisted of baseline scores, whereas follow-up data were used to validate the predictions. The mapping algorithms used ordinary least squares and multinomial logistic regression models to predict the relationship between WOMAC scores, categories, or items and ICECAP-O scores or the 5 ICECAP-O attributes. Results. ICECAP-O scores predicted from WOMAC category scores produced the lowest mapping error statistics (mean absolute error = 0.0832; mean squared error = 0.0142) as well as highest goodness of fit (R2 = 0.3976). Prediction of ICECAP-O attributes from WOMAC category scores was possible for the majority of capability dimensions. The “control” attribute and physical function WOMAC category exhibited the strongest relationship (R2 = 0.2143). The “attachment” attribute proved difficult to predict from any WOMAC category, which is in line with intuition given this attribute captures psychological well-being rather than pain, stiffness, or physical function. Conclusion. This is the first study to investigate the predictive ability of a condition-specific measure of health onto capability. The results presented here suggest it is feasible to map from condition-specific measures to an overall capability index, although WOMAC cannot predict individual capability in its entirety. Although the results here are encouraging for those interested in using ICECAP-O, given the small validation sample size applied, further research will be required to verify these findings.