<p>The current study assesses the aeration efficiency of ten distinct sharp-crested weirs across various discharge rates and drop heights to optimize oxygen entrainment in flowing water. Experimental measurements and high-resolution nappe imagery were used to analyze aeration performance. Findings reveal that the wetted perimeter and nappe characteristics influence the water–air interaction, with smaller wetted perimeter significantly enhancing aeration efficiency. Metaheuristic regression approaches, support vector machine (SVM) (with rbf and poly kernels) and non-linear regression equation (NLRE), were assessed for their applicability to predict the aeration performance. NLRE predicted aeration efficiency within a ± 2% error margin with R² of 0.98, while SVMR with rbf kernel demonstrated strong predictive capability with a mse of 0.002 and R² of 0.92. A sensitivity analysis identified the shape factor as the most influential parameter in model performance. Research findings suggest the applicability of SVM and NLRE and the critical role of nappe in efficiently designing and optimizing sharp-crested weirs for enhanced aeration.</p> Graphical abstract <p></p>