Résumé : Electrochemical nucleation and growth (EN&G) is an inherently dynamic process governed by atomic-level interactions. Understanding the electrochemical phase formation on foreign substrates presents a formidable challenge at the fundamental level. One of the main challenges lies in uncovering both the energetic state of the substrate and the complex interaction between the substrate and the newly formed phase at the “electrode–electrolyte” interface. Furthermore, obtaining direct, unconvoluted, information is not straightforward due to the intricate nature of the phase boundary and phase formation process. In this work, we explore the EN&G from a local perspective by independently probing hundreds of different surface regions with scanning electrochemical cell microscopy (SECCM), providing a novel perspective and insights into the activity distribution and role of the substrate state in the nucleation process. We highlight the significance of acknowledging the diversity at the microscopic scale by summarizing the electrochemical profiles with statistical measures and observing their temporal- or potential-dependent evolution. Our results show that the energy required for the formation of stable nuclei on active sites varies due to surface heterogeneities, significantly impacting the overpotential required on low-energy and high-energy substrates. Upon a cross-system examination, trends emerge thanks to our high-throughput approach. Although nucleation is driven by the most active sites, we observe that it is possible to probe less active sites. Interestingly, these can significantly change their activity after being subjected to polarization. Non-uniform distributions of nucleation activity are disclosed and can be best fitted with two expressions: lognormal and Weibull. The understanding of these distributions is the bridge connecting the microscopic information to macroscopic outcomes, shedding light on how surface heterogeneities influence nucleation rates and deposition behaviors. Characterizing the distribution provides valuable insights into the underlying mechanism, offering a deeper understanding of the nature of active sites and highlighting the capabilities of our local approach for leveraging data-driven analysis.