Interesterification is a fundamental tool in the development of "zero trans" fats. In the production of pan bread, fat contributes to lubrication and an increase in dough extensibility, and an increase in bread volume and flavor. Fat affects texture, maintaining breads soft for a longer period of time; this is possibly due to its interaction with starch in flour, retarding the retrogradation process. The aim of this study was to apply Artificial Neural Network (ANN) technology in the formulation of "zero trans" fats based on soybean oil and soybean interesterified fats to ease the formulation process through blending, for use in bakery products, and determine their influence on the quality of pan bread and on their interaction with starch in flour. For this, pre-mixes and breads with the addition of 4% fat were produced. As standards, commercial fats (hydrogenated soybean fat -GHS and low trans fat -GLT) were used, as well as soybean oil (OLS). The fat blends formulated using the ANN (BL1, BL2, BL3 e BL4) were also used. As control (C), bread without fat addition was prepared. The farinographic analysis showed that water absorption (ABS) of pure wheat flour (59.0%) was in average 6.5% higher than that of the pre-mixes of flour and fats. Dough development time (Td) was lower for the samples GHS, GLT and BL4. The extensographic analysis showed that, amongst all samples, BL4 showed the highest resistance to extension (980 EU) and the lowest extensibility (114 mm). This probably occurred due to the lower soybean oil content in its constitution (54%) that could have contributed to a more consistent dough. The analysis of the breads produced revealed that only the specific volumes of the samples OLS (3.46 mL/g) and BL3 (4.07 mL/g) differed significantly. Firmness analysis of breads showed that throughout the storage period studied there was a significant difference between the firmness of the breads with fats and the control sample (1005.75 gf), being this value 13% higher than that of GHS -the firmest amongst samples with fat. Crumb uniformity was greater with the use of fat. In the control breads (C), porosity (26.73%) was almost 3 times greater than that of the samples with the addition of the blends. The crumbs of breads BL1, BL2, BL3 and BL4 presented small and more uniformly distributed alveoli, when compared to breads C, GHS, GLT and OLS. As to moisture content, breads with fat presented lower values when compared to the control sample (35%), as their doughs absorbed less water during mixing. Thermal analysis through DSC suggested an effect of fat on bread staling, once retrogradation enthalpy changes were lower for breads with fats. The fat blends developed using the ANN and used in this study, as well as having a low trans fatty acid content (1.18% in average), showed feasibility for application in pan bread.