Premise of the Study Access to improved crop cultivars is the foundation for successful agriculture. New cultivars must have improved yields that are determined by quantitative and qualitative traits. Genotype‐by‐environment interactions ( GEI ) occur for quantitative traits such as reproductive fitness, longevity, height, weight, yield, and disease resistance. The stability of genotypes across a range of environments can be analyzed using GEI analysis. GEI analysis includes univariate and multivariate analyses with both parametric and non‐parametric models. Methods and Results The program STABILITYSOFT is online software based on JavaScript and R to calculate several univariate parametric and non‐parametric statistics for various crop traits. These statistics include Plaisted and Peterson's mean variance component ( θ i ), Plaisted's GE variance component ( θ (i) ), Wricke's ecovalence stability index ( W i 2 ), regression coefficient ( b i ), deviation from regression ( S di 2 ), Shukla's stability variance ( σ i 2 ), environmental coefficient of variance ( CV i ), Nassar and Huhn's statistics ( S (1) , S (2) ), Huhn's equation ( S (3) and S (6) ), Thennarasu's non‐parametric statistics ( NP (i) ), and Kang's rank‐sum. These statistics are important in the identification of stable genotypes; hence, this program can compare and select genotypes across multiple environment trials for a given data set. This program supports both the repeated data across environments and matrix data types. The accuracy of the results obtained from this software was tested on several crop plants. Conclusions This new software provides a user‐friendly interface to estimate stability statistics accurately for plant scientists, agronomists, and breeders who deal with large volumes of quantitative data. This software can also show ranking patterns of genotypes and describe associations among different statistics with yield performance through a heat map plot. The software is available at https://mohsenyousefian.com/stabilitysoft/ .