Each new tool has to be tested and characterized in terms of force, stability, and finish quality. This is true also for the newly developed circle-segment tools that have a large engagement (the surface of the cutting section of the tool that is in contact with the workpiece).The Virtual Model of Finish-Machining with Circle Segment End-mills study shows a model that can be used to create a simulation of these tools. By taking the basis of this simulation it is possible to simulate the surface machined by this tool, so it is possible to study how thetool run-out and the vibration affects the machined surface. And so, the aim of this study is to make this simulated surface and observe how the run out of the tools and how the vibration affects the final surface finish quality. To do it the run-out of a real tool has to be measured, and then the profile of this tool including the run-out must be used to create the tool’s profile to simulate the surface. To simulate the surface, a mesh has to be created. The tool’s profile is then put in the movement to mimic the real action of the tool by updating the surface height of the created mesh. Then the result can be compared with a theoretical one without run-out or vibration. Real machined samples could also be made and then observed with white light interferometry inorder to highlight the influence of the two studied parameters on the surface finish. During the machining, the vibration could be measured and could, after, be used to recreate vibration into this model but also to compare the White Light Interferometry observations. With these experiments, we could see how the tool run-out could affect the surface finish by creating stripes patterns of regular sizes but also that vibration is finally a secondary parameter that affects the roughness but not as much as other parameters. The finding given at the end is hard to generalize but can still be compared to other cases, the program in another hand is useable with all kinds of circle segment tools and could even be modified to improve the model we are currently using.