This work systematically investigates the grain topology evolution and hot deformationHot deformation response of additively manufactured 18Ni(300) maraging steelsMaraging steel at a temperatureTemperature range of 850 to 1050 °C and strain rate range of 0.01 to 1 s−1. The flow stress values under experimental deformation conditions were predicted using a Gaussian process regressionGaussian process regression (GPR) model with maximum likelihood parameter estimation approach and compared with an Artificial neural networkArtificial neural networks (ANN) model with a 3–6-6–1 architecture. Results show that columnar prior austenite grains exhibited localized flow deformation behavior and preferential nucleation of recrystallized laths aligned along <111>//BD. The superior performance of the GPR model compared to the ANN model during cross-validation can be attributed to its effective balance in penalizing both model fit and complexity. A net-shape fabrication technique combined with a high temperatureHigh temperature forming route to develop dense structures with controlled local texture is proposed.