We introduced a flexible class of continuous distributions called the generalized KavyaManoharan-G (GKM-G) family. The GKM-G family extended the Kavya-Manoharan class and
provided greater flexibility to the baseline models. The special sub-models of the GKM-G family are
capable of modeling monotone and non-monotone failure rates including increasing, reversed J shape,
decreasing, bathtub, modified bathtub, and upside-down bathtub. Some properties of the family were
studied. The GKM-exponential (GKME) distribution was studied in detail. Eight methods of
estimation were used for estimating the GKME parameters. The performance of the estimators was
assessed by simulation studies under small and large samples. Furthermore, the flexibility of the twoparameter GKME distribution was explored by analyzing five real-life data applications from applied
fields such as medicine, environment, and reliability. The data analysis showed that the GKME
distribution outperforms other competing exponential models.