This work presents a model-based algebraic approach to robust parameter estimation in uncertain dynamics rotating machinery. The approach evades some mathematical intricacies of the traditional stochastic methods, proposing an affordable Jeffcott-model-based scheme with several easy-to-implement computational advantages for processing a real-world rotor frequency response or orbit. Therefore, it takes out the dynamic parameters from one of the orbit's resonant humps when the multistage rotor orbit shape behaves closely to the Jeffcott-model orbit. This occurs for a valuable array of cases. The approach applies the spatial '2-norm looking forward to the correlation between the analytical Jeffcott-orbit model and the experimental rotor's orbit hump, handling the normalized frequency ratio. Experimental results are also included to face this method with real-world rotating machinery orbits.