The present study focuses on predictors that are affecting the child mortality that has emerged as a calamity District Tharparkar, Sindh. The Infant & child mortality was one of the major millennium development goals (MDGs), and also in Sustainable Development Goal 2015-2030, “goal 3, ensure the healthy lives and promote well-being for all at all stages” has got extensive concentration and improvements, nowadays. This situation is excellent in the developed nations as they surprisingly have decreased child mortality rate, but on the other hand, the developing countries, like Pakistan, require a lot of efforts for considerable and extensive reduction in child mortality. However, the child mortality was examined by the researcher himself, and three hundred interviews were conducted for the target population of valid respondents. Cluster sampling technique was applied to collect data from victimized families that were confirmed from the district health department. A scheduled interview was used as a tool which was consisted of structured and semi-structured questions. The findings represent the relationship of child mortality with etiologies such as socio economic factors, nutrition deficiency in infancy, poor child health care by parents, non-availability of medicine, specialists, doctors, and hospitals, as well as drought seasons that had created this disaster in this region. Linear regression model, ANOVA and multiple regression model show that the value of R-Square is 0.493, F-value is 20.85 and overall regression coefficient is significant. The health status of children was explained by the nine variables including education, wife’s education, family structure, income, number of living children, having proper breakfast, eating vegetables in daily nutrition, eating fruits, and taking supplements during pregnancy. This shows that overall model is statistically significant. The overall significance of the model can also be judged by the F-test. The F-value is 20.85 which is significant at less than one percent level of significance. This also suggests that the model is highly significant.
