Assessing and monitoring the welfare of free-living mammals is not a usual process due to the logistical complications associated with their capture and sedation, collection and storage of biological samples and their release. In this context, non-invasive methods for monitoring wildlife constitute a good alternative approach for in situ conservation. Body condition index, as a measurement of health status, has been used in free-living mammals; its low value may be associated with negative effects on reproduction and survival. The present study aimed to generate an alternative and reliable non-invasive method and then determine the body condition index, based on previously-collected biometric measurements, without the need to capture and immobilise the animals. A total of 178 free-living Nasua nasua Linnaeus, 1766 were trapped, weighed and measured. Statistical methods were used, based on Boosted Regression Trees (BRT) using body mass, biometric measurements (body length, height and chest girth) and gender as explanatory variables. To assess the agreement between the real Body Condition Indices (BCIs) and the predicted values of BCIs, we explored the correlation between each model using the Bland-Altman method. This method showed a strong agreement between the predictive BRT models proposed (standardised residuals from a linear regression between body length and chest girth) and standardised residuals (linear regression between body mass and body length). The results obtained herein showed that BRT modelling, based on biometrical features, is an alternative way to verify the body conditions of coatis without the need to capture and immobilise the animals.