The present study aimed to determine some physiochemical and mechanical properties of tomato fruits (commercial variety Jasmin 775), and regression models to estimate volume and mass based on diameters and projected area, which is considered as a database for designers and developer of machine or parts of agricultural smart mechanisms for harvesting, sorting, grading, handling, halving, and slicing. Physical properties were included the axial dimensions, arithmetic diameter, geometric diameter, mass, density, surface area, packing coefficient, sphericity, aspect ratio and draying rate of the tomato fruits. The mechanical properties were studied were the static coefficient of friction and firmness. The results indicated that the model for the prediction of volume based on dimension was , while the model for the prediction of mass based on dimension was  and model for the prediction of mass based on projected area was . The model's equations obtained are important in predicting volume and mass of tomato fruits to designers of post-harvest machines that rely on vision technologies such as handling sorting and grading in food factories and agricultural harvest robots related to this variety.