Inconel 625, a high-strength superalloy with excellent corrosion resistance, discovers wide applications in critical sectors such as aerospace, nuclear, marine, and petrochemical. Single-Point Incremental Forming (SPIF) has appeared as an adequate fabricating process for shaping superalloy components. This work used a systematic approach, implementing Response Surface Methodology (RSM) to explore the influence of SPIF process variables, including tool nose diameter, step size, tool spindle speed, and wall angle, on microhardness (MH) and surface roughness (SR). The experimental results have been analyzed to determine the influencing process variables and their optimal settings, which simultaneously enhance MH and reduce SR of Inconel 625 superalloy truncated cones using analysis of variance and the desirability function analysis approach. The most significant parameters that influence MH and SR were TND and SS, respectively. The development of quadratic models for MH and SR has been completed successfully. The maximum MH of 486.8 HV and minimum SR of 0.432 µm have been obtained at the optimal parametric setting of TND = 15 mm, SS = 0.4 mm, TSS = 900 rpm, and WA = 57.5° with the desirability values for MH, SR and combined are 0.832, 0.933, 0.881 respectively. The F-value of the MH model = 109.18 and SR Model = 78.24 implies that both models are significant and both models have excellent prediction strength. The percentage error between predicted and actual values of MH and SR in confirmation run results is less than 5 %. •This study introduces the SPIF of Inconel 625, extending its use to critical sectors like aerospace and nuclear demand for high-performance materials, marking a novel approach to fabricating conical shapes.•Utilizing RSM, the research systematically investigates the impact of SPIF process variables on the microhardness and surface roughness of Inconel 625, setting a standard for Inconel 625 superalloy forming.•The study optimizes SPIF parameters to simultaneously improve the microhardness and reduce the surface roughness in Inconel 625 components, showcasing a balanced approach for quality enhancement.•The computation and validation of quadratic models for predicting microhardness and surface roughness based on SPIF parameters represent a major advancement, which shows significant prediction capability with less than 5 % prediction error.•The research identifies critical SPIF parameters and their optimal settings to achieve targeted responses in Inconel 625 components, offering practical guidelines for industry application and enhancing surface quality.