Our purpose is to provide an augmented reality system for Radio-Frequency (RF) tumor ablation guidance that could superimpose a 3D model of the liver, its vessels and tumors (reconstructed from CT images) on external video images of the patient. The main constraints are the reliability and the accuracy, which justifies a 3D/2D registration based on radio-opaque fiducials rather than surface- or 3D- based techniques. Then, a lack in the statistical assumptions of the classical 3D/2D registration methods led us to the derivation of a new extended 3D/2D criterion. Careful validation experiments on real data show that an accuracy of 2 mm can be achieved in clinically relevant conditions, and that our new criterion is up to 9 computation time compatible with real-time at 20 to 40 Hz. However, the accuracy of the registration strongly vary w.r.t. the experimental conditions (cameras angle, number of markers...). Thus, to provide a safe system, we should supply an error prediction that take this parameters into account. Propagating the data noise through both our criterion and the classical one, we obtain an explicit formulation of the registration error. As the real conditions do not always fit the theory, it is critical to validate our prediction with real data. Thus, we perform a rigorous incremental validation of each assumption using successively: synthetic data, real video images of a precisely known object, and finally real CT and video images of a soft phantom. Results point out that our error prediction is fully valid in our application range. Eventually, we provide an accurate RA guidance system that allows the automatic detection of potentially inaccurate guidance.