This study evaluates the performance of doubles-corrected random phase approximation (RPA) and higher random phase approximation (HRPA) approaches in predicting nuclear magnetic resonance (NMR) coupling constants involving fluorine. Their performance is benchmarked against experimental data and compared with that of higher-level theoretical methods, specifically second-order polarization propagator (SOPPA) and SOPPA(CCSD). Additionally, we discuss their performance relative to density functional theory (DFT). We find that RPA(D) is severely constrained by (near) triplet instabilities, while HRPA(D) demonstrates markedly improved stability. Statistical analysis reveals stronger patterns for carbon-fluorine couplings across the methods and systems investigated compared with fluorine-hydrogen couplings. While SOPPA-based methodologies prove to be superior in accuracy, HRPA(D) shows promising performance in reducing the computational burden of these calculations, albeit with a tendency to underestimate the coupling strength. These findings highlight the potential of HRPA(D) as a practical alternative to SOPPA methods, even for such difficult properties as NMR spin-spin coupling constants involving fluorine, emphasizing its role in improving predictive accuracy and efficiency across diverse chemical environments.