The convergence of fast fashion and e-commerce has led to a sustainability crisis characterized by high return rates primarily driven by poor fit. To improve clothing retention rates, the industry must enhance garment fit for individuals, however, current mass production practices hinder this goal. Recent technological advancements offer potential solutions to this challenge. Body scanning technology, Computer-Aided Design (CAD) software, and automated manufacturing systems have created an environment where individuals can produce tailored garments that meet their preferences without the high costs typically associated with bespoke tailoring. However, these solutions still require pattern-making or technical knowledge, limiting their accessibility. To bridge this knowledge gap and make patternmaking more approachable, solutions need to combine the 'What You See Is What You Get' (WYSIWYG) garment design approach with a responsive pattern-making function – also known as a 3D to 2D pattern making. This master's thesis aims to increase accessibility to custom-made (bespoke) clothing by designing methods and tools that utilize body scan technology to allow users to create 3D clothing models that are quickly developed into their resulting garment patterns. In both studies, the proposed methods were developed and tested on skirts. The cylindrical shape of a skirt makes it simple to model while still allowing for aesthetics that can contour the body (positive curvature) or create fullness (negative curvature).The first 3D to 2D approach outlined in the thesis is Virtual Draping and Flattening (VDF). To test the method under positive and negative curvature, the study created a mermaid skirt, equivalent to a six-gored skirt, fitted until the mid-thigh. VDF combines Rhino, Rhino's plug-in Grasshopper, and Sawhney and Crane's (2017) Boundary First Flattening (BFF) program. At a high level, the method consists of modeling the skirt from the body scan, drawing seams and splitting the surface, and flattening the individual pattern pieces using BFF. Long meandering seams were used in the process to better contour the body. Compared with a similar garment constructed using a conventional pattern-making approach (Joseph-Armstrong, JA), the participant noted that the VDF skirt provided a better fit but did not successfully provide better balance in the waist, hem, and drape profile than the JA skirt. The long meandering seams did create visual interest and, in conjunction with the body scan, improved the fit of the garment in areas underserved by the conventional garment. However, the complexity of the seam caused construction errors, which negatively impacted the fit. The VDF process required a high level of technical expertise, shifting the burden of knowledge from understanding traditional patternmaking to mastering software tools like Rhino and BFF. As a result, the process did not alleviate the user's workload but instead replaced one form of complexity with another. The second study was developed in response to the shortcomings of VDF. Skirter is an end-to-end pattern drafting platform developed in Rhino's plug-in Grasshopper that references the body scan to build a 3D garment that includes anthropometric features and automatically drafts the pattern. To reduce room for error, the garment aesthetic was simplified to a straight skirt. Skirter aims to mimic the conventional pattern for skirt garments, creating patterns with two seams (one at each side) and four darts (two in the front and two in the back). Skirter's workflow consists of four steps: Body Scan Cleaning & Preparation, Automatic Landmarking, Building the 3D Wireframe, and Drafting the Garment Pattern. Tested on 20 participants, Skirter developed garment patterns for 19, and sixteen participants returned to evaluate the fit of the Skirter-generated garment. Fit analysis revealed common issues, such as horizontal folding and diagonal wrinkles, attributed to tightness around the abdomen and high hip areas. Despite these challenges, Skirter produced skirts that provided a consistent fit aesthetic across various body shapes and BMIs. This work demonstrates that with continued development, tools like Skirter can bridge the gap between mass production and bespoke tailoring by offering a scalable solution to customize garment fit. By incorporating advanced algorithms and leveraging the increasing availability of body scan data, this technology has the potential to transform the apparel industry cutting down on returns, promoting better fitting, and even placing garment creation in the hands of the user.