We theoretically investigate reversible adsorption in electrochemical devices on a molecular level. To this end, a computational framework is introduced, which is based on 3D random walks including probabilities for adsorption and desorption events at surfaces. We demonstrate that this approach can be used to investigate adsorption phenomena in electrochemical sensors by analyzing experimental noise spectra of a nanofluidic redox cycling device. The evaluation of simulated and experimental results reveals an upper limit for the average adsorption time of ferrocene dimethanol of ∼200 μs. We apply our model to predict current noise spectra of further electrochemical experiments based on interdigitated arrays and scanning electrochemical microscopy. Since the spectra strongly depend on the molecular adsorption characteristics of the detected analyte, we can suggest key indicators of adsorption phenomena in noise spectroscopy depending on the geometric aspect of the experimental setup.