<p>Several aerospace components are made from Udimet 720 alloy, which is primarily suitable for high-temperature applications. These superalloys constitute an essential class within the broader family of superalloys, with nickel as the primary alloying element. This work uses additive manufacturing (AM) technology to print the required sample for experimental studies. Udimet alloy 720 can be additively manufactured to create high-performance components with optimum weight, shape, and mechanical properties. After production, several post-processing procedures are required, such as removing components from the build platform. This crucial procedure must be completed quickly, accurately, and with an appropriate surface finish. Using the wire cut electrical discharge machining (WEDM) technique, the machinability properties of the additively manufactured Udimet 720 alloy are investigated. Surface roughness is used to assess the quality of the machined surface, whereas overcut is used to evaluate accuracy. Descriptive and inferential statistical techniques are used to examine the process parameters' effects on surface roughness and overcut indexes. The experimental studies are based on the design of the experiment concept. The L₂₇ orthogonal array model is used based on the number of parameters. The selected parameters are the pulse – on time (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(T_{{{\text{on}}}}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>T</mi> <mtext>on</mtext> </msub> </math></EquationSource> </InlineEquation>), gap voltage (<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(V\)</EquationSource> <EquationSource Format="MATHML"><math> <mi>V</mi> </math></EquationSource> </InlineEquation>), peak current (<i>I</i>), pulse – off time (<InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(T_{{{\text{off}}}}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>T</mi> <mtext>off</mtext> </msub> </math></EquationSource> </InlineEquation>), and wire tension (<InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(W_{T}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>W</mi> <mi>T</mi> </msub> </math></EquationSource> </InlineEquation>) and wire feed (<InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(W_{F}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>W</mi> <mi>F</mi> </msub> </math></EquationSource> </InlineEquation>) on surface roughness (<InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(R_{a}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>R</mi> <mi>a</mi> </msub> </math></EquationSource> </InlineEquation>) and overcut (<i>OC</i>). The combinative distance-based assessment (CODAS) technique is used to find the optimal setting to get the preferred surface roughness and overcut. (CODAS) analysis and its relative assessment grades predict the optimal condition as A3B3C3D1E2F1. This optimal level decreases the surface roughness and overcut by 23.18 and 19.82%. Furthermore, pulse–on time, pulse–off time, wire tension, and voltage significantly influence relative assessment grades.</p>