**5. Conclusions**

In summary, (1) we found the strongest predictors of running velocity, (2) we derived novel prediction models for running velocities in accordance with TRIPOD guidelines, and (3) we established their fair validation.

Currently, with the use of a machine-learning approach, we can accurately estimate VAT, VRCP, and Vmax based only on somatic and exertion variables (the precision and repeatability in the study subgroups were comparable to the test-retest error). VO2, [La−]b, VE, and somatic characteristics were the greatest contributing factors. We anticipate that our findings will improve the personalization of training and rehabilitation programs. Models should be primarily applied in disciplines where running is the main form of activity, due to the similar characteristics to those regarding the specificity of the derivation cohort.

**Supplementary Materials:** The following supporting information can be downloaded at: https://www. mdpi.com/article/10.3390/jcm11226688/s1, Supplementary Material S1: TRIPOD Checklist: Prediction Model Development and Validation.

**Author Contributions:** Conceptualization, S.W.; methodology, S.W. and M.M.; writing—original draft preparation, P.S.K. and S.W.; software and statistics, I.C. and S.W., writing—review and editing, P.S.K., S.W. and M.M.; supervision, D.S. and A.M. All authors have read and agreed to the published ´ version of the manuscript.

**Funding:** The authors received no funding from an external source.

**Institutional Review Board Statement:** The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review of the Bioethical Committee at the Medical University of Warsaw (AKBE/32/2021).

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

**Conflicts of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
