For each target, we sampled molecules using multinomial sampling (MNS with sample size 3x 20) and applied molecular weight filters to ensure the generated molecules matched these key properties of the target compound. After sampling we employed the HSQC matching methodology developed in our previous research, using the HungDist-NN matching algorithm to score and rank the set of sampled molecules. Additionally, we applied the same point matching methodology for the COSY spectrum and investigated its impact on molecule ranking. Evaluation uses three ranking methods: COSY, HSQC, and combined HSQC & COSY, with top-k accuracy calculated for k = 1, 3, 5, 10, 20 and "Total" representing all generated molecules out of the maximum of 60 sampling options. Results for the MMT model, illustrated in Figure , show near-perfect accuracy on our simulated data (a-c), with already top-3 accuracy reaching 100% across all ranking methods. Performance on ACD Labs simulated data (d-f) remains strong, with top-3 accuracy of 67% and reaching 94% for top-20. Experimental data (g-i) shows similar performance, with top-3 accuracy between 62% and a total top performance of 94% over all sampled molecules. Notably, the combined HSQC & COSY ranking outperforms individual rankings across all data types, suggesting enhanced prediction accuracy. For instance, in experimental data, the combined ranking achieves 91% top-10 accuracy compared to 88% for COSY or HSQC alone.