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Soil nitrous oxide (N₂O) fluxes are commonly measured with nonsteady state chambers using slope values derived from linear or quadratic regression, fitted to the change in N₂O concentration over time (dC/dt); however, these methods frequently underestimate N₂O flux values. Here, we propose a decision tree-based model (DTBM) to better match curve shape with linear and nonlinear models to estimate dC/dt. The DTBM was compared with linear, quadratic regression, and the Hutchinson–Mosier (H–M) equation. The objectives were to (i) evaluate curve shape classification; (ii) evaluate dC/dt response to uncertainty, and (iii) determine method effect on cumulative N₂O emissions and emission factor. Curve shapes with increasing N₂O concentration over time had the highest proportion of data (52%–55%). Mean N₂O flux calculated with DTBM showed to be less responsive to data variability, and therefore, more …