The quality of Surface-Enhanced Raman Chemical Imaging (SER-CI) rely on several parameters, among which the uniform deposition of metallic nanoparticles impacts greatly the result. Optimizing deposition protocols for biological samples is challenging due to inherent spatial heterogeneity, preventing the distinction between deposition artefacts and true analyte distribution. However, to optimize the deposition parameters, it is necessary to have a controlled experimental model. This study presents the development of a repeatable dried gelatine–agarose hydrogel as a controlled analytical substrate with the uniform spatial homogeneity of diphenhydramine hydrochloride as the experimental model for further nanoparticle deposition optimization. With its skin-mimicking Raman fingerprint, the proposed hydrogel enables the systematic evaluation of deposition techniques without biological variability. Confocal Raman imaging performances are as follows: the normalization-based ratio (I₁₀₀₃/I₁₄₆₉) achieved an intra-day RSD of 3.6–8.2%, inter-day RSD of 6.5%, and intra-day pixel-wise RSD (%) of 8.3–12.3%. The Distribution Homogeneity Index (DHI) confirmed the analyte’s uniform distribution. Drying kinetics modelling revealed a diffusion-based dehydration process, with repeatable batch production. Application of dried hydrogels for SERS chemical imaging confirmed diphenhydramine hydrochloride detectability inside the polymeric matrix, with the proportionality of intensity based on the diphenhydramine hydrochloride concentration. A preliminary performance comparison of nanoparticle deposition by drop-casting and spray-coating demonstrates the applicability of the developed model. This standardized matrix provides a reference platform for evaluating deposition homogeneity, distinguishing method performance from sample artefacts and accelerating chemical imaging method development and performance through optimization.