<p>Ti6Al4V is considered a promising candidate material for bioimplant applications, including bone implants, skull covers, and surgical equipment, due to its high specific strength and non-reactive nature with human body fluids. The aim of this study is to understand the effect of in-situ heat treatment on flow stress behavior, thereby to eliminate the need for traditional heat treatment methods, thereby reducing costs associated with equipment, time, and energy consumption. In the present study, the flow stress behavior of Additive Manufacturing (AM) Ti–6Al–4V alloy was investigated using two different sample preparation methods: single scanning and in-situ heat treatment (double scanning), aimed at controlling the mechanical properties during fabrication via the selective laser melting (SLM) process. Using analytical techniques such as Field emission scanning electron microscopy (FESEM) and Electron Backscatter Diffraction (EBSD) images the phase present such as α, β, α′, and α + β and their evolution mechanisms were discussed critically in single scanned and in-situ heat treatment. The uniaxial tensile tests were carried out at different quasi-static strain rates in a range of 0.001 to 1&#xa0;s⁻¹ and dynamic strain rates in the range of 10 to 500&#xa0;s⁻¹. Further, improved version of the Johnson–Cook model has been formulated by using the experimental parameters for the Ti6Al4V alloy, furthermore, an artificial neural network-based (ANN) predictive model was established to evaluate the flow stress response of the Ti–6Al–4V alloy across diverse loading conditions. The results demonstrated that the AI-based ANN model performs comparably to the modified Johnson–Cook model, with the predicted flow stress values showing strong agreement with those obtained using the Johnson–Cook (J–C) formulation.</p>