Aggregation of silver nanoparticles (AgNPs) induced by halide ions has been widely exploited within the surface-enhanced Raman scattering (SERS) applications, acting as adions for improved detection of specific analytes. Both cations and anions exert influence on SERS and studies so far have focused on salt concentrations ranging within millimole range to induce optimal AgNPs aggregation. Here we employed hypersaline solutions (1-2 M, with 0.2 M increments), simulating the salinity levels of hypersaline environmental waters, without considering additional contributors, and demonstrated that SERS can be reliably used to estimate the salinity of such samples. We employed the strong interaction between excessive chloride ions and citrate-reduced AgNPs surface to investigate the SERS signal variability, focusing on the Ag/Ag-Cl SERS band at 231 cm⁻¹ over time, starting from the moment the saline solution was mixed with AgNPs until a stable plateau of maximum intensity was reached (240 minutes). The complex physicochemical mechanisms of AgNPs aggregation enabled the time-dependent intensity plot of the 231 cm-1 band as a function of saline solution concentration. A calibration curve against concentration based on exponential function fitting of the SERS dataset allowed to calculate the concentration of unknown hypersaline solutions. The calibration curve corresponding to ten minutes after mixing solutions proved to be the most accurate, with an R² value of 0.99, with relative error < 1.5% for NaCl concentration estimates. These results expand the SERS applicability for fast, in situ salinity estimation in hypersaline aquatic environment.