The bladed rotor is an important part in turbine machines. Timely detection of its blade rubbing fault may avoid serious accidents. This paper developed a rub-impact fault identification approach for the bladed rotor based on chaotic features such as average period, time delay, embedded dimension, and largest Lyapunov exponent. A dynamic analytical model of a rotating variable thickness blade with the rub-impact fault is established. It is verified that the blade rubbing model could obtain the relationship between the chaotic behaviors and the rub-impact fault for a rotating blade. Through the nonlinear characteristic analysis, we could establish that different blade rubbing states have a certain corresponding relationship with the chaotic characteristics, which provides the theoretical basis for the blade rubbing identification using the chaotic features. In particular, a rub-impact fault identification approach based on chaotic features is further studied. And the blade rubbing fault can be easily identified by combining four chaotic features, which is proven by experiments. Comparing with the time domain and frequency domain analysis methods, the proposed approach provides a new way to identify such blade rubbing fault.