Machining parameters needed for stable, high-performance high-speed machining could be found using mathematical models that need accurate measurements of modal parameters of the machining system. In-process modal parameters, however, can slightly differ from those measured offline and this can limit the applicability of simple measurement methods such as impact hammer tests. To study and extract the in-process modal parameters, mathematical models are used to define two key dimensionless parameters and establish their relationships with each other and the modal parameters. Based on these relationships, the modal parameters are extracted using two analytical methods, the two-point method (TPM), and the regression method (RM). As shown with experimental studies, the RM extracts the modal parameters successfully and while being much faster than the existing iteration-based methods, it provides stability lobe predictions that match well the experimental results. Furthermore, it is noted that the natural frequency parameter is estimated with much better relative precision compared to the damping ratio and the modal stiffness parameters. © 2019 Elsevier Ltd