Arterial stenosis is a prevalent disease worldwide that affects millions of people in Brazil, and its diagnosis currently depends on invasive or inaccurate tests. Therefore, the search for non-invasive methods is essential. Using the Windkessel model, the SINDy algorithm was used to estimate mechanical parameters with possible physiological significance in the arterial system. For this work, virtually generated aortic flow waves were used to simulate pressure waves for each virtual subject. Using these aortic arterial pressure data and flow waves, with signals obtained from open databases (n = 50), the algorithm was able to identify the electrical parameters of resistance and compliance of the electrical model. The influence of the data acquisition frequency on obtaining the resistance and compliance parameters was also verified. The parameters obtained were close to the simulated values, with mean values of R = 0.556 ± 0.041 mmHg.s.mL−1 (mean ± standard deviation) and C = 2.342 ± 0.056 mL.mmHg−1, with a percentage difference of 4.88 ± 0.84% and 3.12 ± 0.17%, respectively, when compared to the parameters used to generate the data. The regularization parameter λ was optimized using a Pareto chart, using λ = 0.3. In addition, reducing the sampling frequency of the data still showed results close to those expected, but with divergences when making this frequency too low. Therefore, these results suggest that the SINDy algorithm can be a tool used to better understand hemodynamic systems.