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Sowing quality, determined by the uniformity of seed distribution over area and depth, is a critical factor in crop yield. Existing agrotechnical requirements for seeders are empirical in nature and do not take into account the probabilistic nature of the seeding processes, which complicates an objective assessment and comparison of the quality of different designs. In this regard, the aim of this study is to develop a probabilistic-statistical model for standardizing the sowing uniformity indicators of vegetable seeders based on an analysis of random process outliers beyond acceptable levels. The study utilizes the apparatus of the theory of random processes. Probability characteristics were adapted: the relative duration of exceeding a specified level and the average frequency of outliers. Analytical dependencies were obtained linking the agrotechnical tolerance (β), the probability of its observance (P), and the variation coefficient for the normal and gamma distributions, adequately describing the processes of seed distribution by depth bc(L) and by row length xc(L), respectively. Calculations were performed using the Laplace functions and the incomplete gamma function. It was established that for the process of seed placement depth bc(L), which has a normal distribution, with a tolerance of β = 0.1 and a probability of P = 0.6–0.9, the permissible variation coefficient should be in the range of 4–11%. For the process of distribution of intervals xc(L), described by a gamma distribution, with an agrotechnical requirement of P = 70% and a tolerance of β = 0.5, the permissible value of the variation coefficient was set equal to 50%. A comparative analysis was conducted, which showed an insignificant discrepancy in the estimates of P for the normal and gamma distributions. This allows the use of simpler relationships for the normal law in practical engineering calculations of seeding uniformity with sufficient accuracy.