The use of non-traditional types of flour in the production of bread and bakery products is an urgent scientific and practical task of baking, which allows to obtain products with functional properties, high quality and safety indicators, as well as for medical and medical and preventive nutrition. As unconventional raw materials one proposes usage of chickpea flour (TU 9293-009-89751414-2010 «Pea flour, chickpea flour, lentil flour»), which is distinguished by better food and biological value in comparison with prime grade wheat flour. However, complete replacement is not possible without adding additional raw materials to the formulation to replace the gluten, retaining moisture and creating a gel-like mass. Psyllium has such properties (TU 10.61.40-044-172744632018 «Psyllium of plantain husk»). For this, the authors set a goal - to develop a computer program with elements of artificial intelligence, which allows determining the best areas of organoleptic indicators of bread quality using unconventional plant raw materials. The mathematical modeling carried out helped to determine the area in which the estimates of the appearance, consistency, taste, smell of the model samples were the best, depending on the number of ingredients added. The obtained data formed the basis for compiling a recipe of chickpeas bread with the subsequent development of a cooking technology, which includes kneading dough, proofing it and baking model samples. The program showed good convergence of the obtained results with the real data of laboratory developments, which proves not only the scientific novelty of the experiment, but also the practical significance of the work.