<p>Strontium hexaferrite (SrFe₁₂O₁₉) nanopowders were synthesized via gaseous heat treatment and re-calcination process (GTR), and the effects of high-energy milling time (0, 10, and 20 h), before the re-calcination stage, and calcination temperature (0–1200&#xa0;°C) on the structural and magnetic properties were investigated using XRD, SEM, and VSM methods. A machine learning (ML) approach was used on the experimental data to find the best model for prediction of magnetic properties. Nine ML models were developed on the data, and the support vector regression (SVR) model performed well with an R² score of 0.94, 0.91, and 0.94, and had a small error with an RMSE of 4.59, 3.04, and 0.32 for predicting the saturation magnetization (M_s), magnetic remanence (M_r), and coercivity (H_c), respectively. The selected SVR models were validated with a distinct experiment and showed a high ability to generalize to new data with experimental results of 30.98 emu g⁻¹, 19.46 emu g⁻¹, and 3.68 kOe versus model predictions of 32.01 emu g⁻¹, 19.44 emu g⁻¹, and 4.12 kOe for M_s, M_r, and H_c, respectively. The experimental results showed that by 20 h of milling, the magnetic properties of SrFe₁₂O₁₉ nanopowders improved at lower calcination temperatures, which is due to greater fineness and greater uniformity in particle size and size distribution after milling.</p>