In situations of negative energy balance (NEB) due to feed scarcity or high physiological demands, body energy reserves (BR), mainly stored in adipose tissues, become the main sources of energy for ruminants. The capacity to mobilize and restore such BRs in response to different challenges is of major concern in the current context of breeding for resilience. Body condition score (BCS) is a common, practical indicator of BR variations throughout successive productive cycles, and quantitative tools for characterizing such dynamics at the individual level are still lacking. The main objective of this work was to characterize body condition dynamics in terms of BR mobilization and accretion capacities of meat sheep during their productive lifespan through a modelling approach, using BCS measurements. The animal model used in this work was the reproductive meat ewe (n = 1478) reared in extensive rangeland. Regular measurements of BCS for each productive cycle were used as the indicator of BR variations. A hybrid mathematical model and a web interface, called PhenoBR, were developed to characterize ewes’ BCS variations through four synthetic and biologically meaningful parameters for each productive cycle : BR accretion rate , BR mobilization rate , plus the time of onset and the duration of the BR mobilization, and , respectively. The model PhenoBR converged for all the ewes included in the analysis. Estimation of the parameters indicated the inter-individual variability for BR accretion and mobilization rates, and the length of the mobilization period. The present study is a proof of concept that the combination of data-driven and concept-driven models is required for the estimation of biological meaningful parameters that describe body reserves dynamics through consecutive productive cycles. Individual characterization of animals by these parameters makes it possible to rank them for their efficiency in the use of body reserves when facing NEB challenges. Such parameters could contribute to better management and decision-making by farmers and advisors, e.g. by adapting feeding systems to the individual characteristics of BR dynamics, or by geneticists as criteria to develop future animal breeding programs including BR dynamics for more robust and resilient animals.