Livestock farming is experiencing a period of increasing uncertainty. This uncertainty is, in itself, nothing new. Still, the multiplicity of the parameters concerned, their interactions and the speed with which they change are impacting the decisions farmers must make in terms of herd size, composition and culling. These decisions are increasingly envisioned as major source of endogenous uncertainty which can drive livestock systems toward unsustainable transitions. As complex systems, livestock systems may havecritical thresholds—so-called tipping points—atwhich the systemshifts abruptly from one state to another.Identifying management decisions preventing to reach such tipping points is crucial to improve our understanding of livestock system resilience. The objective of this study was to explore tipping points and resilience in livestock herds under climatic and market uncertainties. Wedeveloped a simple dynamic herd model. The modelis based on Viability Theory which provides mathematical tools for the analysis of system dynamics under constraints. Using this framework we predicted viable management decisionsrespecting a given set of constraints. These constraints definedthresholds, i.e. the limits within which the system should be maintained to remain sustainable. We studiedthe relative weight of exogenous (climate, market) and endogenous uncertainties (management decisions) on herd dynamics and resilience. We identified indicators that could be used as early-warning signals. Using the time of crisis algorithm, we revealed trajectories that minimize the time during which critical thresholds are violated. We explored which herd composition providesthe best insurance against market and climate uncertainties. Finally we discuss which major changes in herd management could reinforce theherd’s ability to face a changing environment.