Feature lines are perceptually salient features on 3D meshes. They are of interest for 3D shape description, analysis and recognition. Their detection is a necessary step in several feature sensitive mesh processing applications such as mesh simplification, remeshing or non-photorealistic rendering. In this paper, an estimator for the angle between tangent plane normals is introduced and a new automatic method is proposed for robust detection of crest lines on 2-manifold triangular meshes, in particular Computer- Aided Design models. The method integrates learning into a global minimization framework favoring geometrically coherent solutions. We study our method in detail and compare it with other methods for the detection of feature edges on 3D meshes. Our comparative results indicate that our method outperforms classical techniques especially in the presence of noise.