Bladder cancer, a malignancy of the urinary tract, has shown a rising incidence rate in recent years. Current diagnostic methods often suffer from issues such as invasiveness, high costs, or insufficient sensitivity, creating an urgent need for a fast, simple, and non-invasive diagnostic approach. In this study, a novel diagnostic method for bladder cancer is proposed, using hyaluronic acid-coated silver nanoparticles (HA-AgNPs) as the substrate for surface-enhanced Raman scattering (SERS) to detect hyaluronidase (HAase), a biomarker for bladder cancer, in urine. This method is based on the hydrolysis of hyaluronic acid on HA-AgNPs by HAase, which generates oligomers and causes the breakdown of HA-AgNPs into smaller nanoparticles. The formation of oligomers enhances the surface shielding effect of the silver nanoparticles, promoting aggregation between particles and significantly weakening the SERS signal. By detecting changes in the SERS signal using Rhodamine (R6G), HAase was quantified. The experimental results show that there is a good linear relationship (R2 = 0.9991) between the SERS signal and the HAase concentration in the range of 3 × 10-4 U/mL to 3 × 101 U/mL. The method demonstrates high sensitivity and can effectively detect HAase concentration in urine. Combining principal component analysis (PCA) with linear discriminant analysis (LDA), effective classification of SERS spectra from 42 normal and 40 bladder cancer urine samples was achieved. Experimental results show that the sensitivity and specificity of this algorithm in distinguishing between the normal and bladder cancer groups reached 95.2 % and 95 %, respectively.