Iron, a principal element of Earth’s core, is vital for understanding the thermodynamic properties of this region. The accuracy of iron’s equation of state (EOS) is crucial, yet experimental uncertainties significantly impact the EOS parameters. By employing Bayesian statistics and Markov Chain Monte Carlo (MCMC) simulations, we have quantified these uncertainties. Our approach introduced a straightforward yet effective method to calculate the probability of phase boundary data. The resulting EOS reliably reproduces a variety of experimental datasets, including phase boundary experiments, static pressure measurements under various conditions, shock wave data, and sound velocity under different states. Using 100 sets of posterior parameter samples, our predictions indicate that the density deficit in Earth’s outer core ranges approximately from 8.7% to 9.7%. Additionally, the inferred geodynamo power output from latent heat release during the cooling and solidification process of Earth’s inner core is estimated to be between 0.458 and 6.002 terawatts.