The growing reliance on nature-based solutions for climate change mitigation has increased the need for robust methods to assess soil greenhouse gas (GHG: CO₂, CH₄, N₂O) emissions. A key challenge is the upscaling of site-specific observations to improve predictions of the spatial distribution and magnitude of soil GHG fluxes. Upscaling is hindered by the laborious, costly, and time-consuming nature of soil flux measurements at the scale needed to generate sufficiently large datasets. Fourier-transform infrared (FTIR) spectroscopy is a cost-effective, high-throughput method that has demonstrated its ability to predict soil physicochemical properties. Since the magnitude of soil GHG fluxes is strongly influenced by these properties, FTIR may also serve as a basis for predicting soil GHG fluxes. In this study, we evaluated whether FTIR calibration models can be developed to predict soil GHG fluxes and organic matter decomposition rates directly from mid-infrared spectra. FTIR calibration and cross-validation were performed using soil samples collected across 20 wetland study sites in six European countries and linked to measured soil GHG fluxes and decomposition rates at the corresponding sampling sites. The results demonstrated that FTIR can be calibrated to reliably predict soil decomposition rates and heterotrophic respiration standardised at a given soil temperature. For decomposition rates, the root mean square error (RMSE) of FTIR-predicted values was 0.01 dd⁻¹, corresponding to approximately 17–53 % of the interquartile range of observed rates. For heterotrophic respiration, the RMSE of 18 mg CO₂–C m⁻² h⁻¹ corresponded to 21–64 % of the interquartile flux range. The findings also indicate FTIR's potential to identify biogeochemical risk areas or potential hotspots of CH₄ and N₂O emissions, effectively mapping the substrate-driven 'ultimate' controls even when 'proximate' environmental triggers (e.g., water table fluctuations) are absent.