Supported nanostructured electroactive materials are known to boost the efficiency of electrocatalytic processes. Although they can be fabricated by multiple methods, electrodeposition offers several advantages, since the nanostructures are grown on the final support. During the last years, we have developed an approach based on using carbon coated TEM grids (CCTGs) as electrodes to better understand electrochemical nucleation and growth mechanisms on the nanoscale. This way, by combining atomic-scale TEM characterization with electron tomography and electrochemical measurements, we have found evidence that has led us to suggest an electrochemical aggregative growth mechanism [1]. It includes nanocluster self-limiting growth, surface diffusion, aggregation and coalescence as important elementary steps of the electrochemical growth process [2,3]. In this context, we have employed the same approach to study the electrodeposition and electrochemical stability of dendritic nanoparticles with large surface areas [4,5], as well as electrochemical nucleation and growth phenomena in Deep Eutectic Solvents (DESs). Special attention is given to the interaction between the solvent and the electrodeposited phase and the role of water since DESs are highly hygroscopic and water cannot be completely removed [6-8]. Due to the high level of complexity of the electrodeposition process and the small timescales and lengthscales that need to be considered, electrochemical and surface characterization techniques feature inherent limitations. Therefore, a complementary approach based on numerical simulations is being evaluated. We have introduced a novel modelling approach that couples a Finite Element Method (FEM) with a random walk algorithm, to study the early stages of nanocluster formation, aggregation and growth, during electrochemical deposition. This approach takes into account different factors: not only the overpotential, but the transport of active species and electrochemical kinetics are also evaluated, together with the surface diffusion and aggregation of adatoms and small nanoclusters [9]. The combined analysis of experimental and simulated data reveals that the relative surface mobility of nanoclusters compared to this of the adatoms plays a crucial role in the early growth stages. The number of clusters, their size and size dispersion are influenced more significantly by nanocluster mobility than by the applied overpotential itself. As a result, an accurate representation of the number of clusters with time, N(t), in potentiostatic electrodeposition should consider, not only an induction time that precedes cluster formation, but also the balance between cluster formation and aggregation. We show that an evaluation of N(t), which neglects the effect of nanocluster mobility and aggregation, induces errors of several orders of magnitude in the determination of nucleation rate constants. These findings are highly important towards properly evaluating the elementary electrodeposition processes, considering not only adatoms, but also nanoclusters as building blocks.