This research presents a preliminary study on finding predictable methods of controlling the self-folding behaviors of weft knit textiles for use in the development of smart textiles and garment devices, such as those with shape memory, auxetic behavior or transformation abilities. In this work, Shima Seiki SDS-One Apex computer-aided knitting technology, Shima Seiki industrial knitting machines, and the study of paper origami tessellation patterns were used as tools to understand and predict the self-folding abilities of weft knit textiles. A wide range of self-folding weft knit structures was produced, and relationships between the angles and ratios of the knit and purl stitch types were determined. Mechanical testing was used as a means to characterize differences produced by stitch patterns, and to further understand the relationships between angles and folding abilities. By defining a formulaic method for predicting the nature of the folds that occur due to stitch architecture patterns, we can better design self-folding fabrics for smart textile applications.