Nonlinear models contain terms where variables multiply or appear with powers >1, producing feedback, bifurcations, and sensitive dependence on initial conditions. Unlike linear models, their predictability is limited, parameter changes can cause qualitative shifts, and solutions cannot generally be superposed.