In this work we describe a generic algorithm (which we call MSFIT) able to estimate the pose and deformations of 3D models of biological structures (bacteria, cells, etc.) with images obtained by optical and scanning electron microscopes. The algorithm uses a image comparison metric multi-scale, that is outline-sensitive, and a novel nonlinear optimization method. In our tests with models of moderate complexity (up to 12 parameters) the algorithm correctly identifies the model parameters in 60-70% of the cases with real images and 80-90% of the cases with synthetic images.