Poverty means different things to different people. There are many different approaches to defining poverty but the basic needs approach is commonly applied, particularly in developing countries where a bigger majority of the people struggle to attain a predetermined minimum level of income to satisfy their basic needs. The research study on “An assessment of magnitude and correlates of Poverty in Jhang District” was carried out with the objective to document the status and trend analysis of poverty situation in all four sub-districts of Jhang District, Punjab. It is an attempt at estimating the incidence, intensity and severity of poverty and identified the determinants of poverty as well the poverty coping strategies among the households in Jhang district. (A medium size city of Punjab Province, Pakistan.). The analysis of the study carried out on the basis of primary data and all data have been collected through a specifically designed questionnaire with a sample of 1000 households in its background in the selected villages of all four sub districts (Tehsil) of Jhang District, Punjab. This study has used bivariate and Multivariate analysis (income regression model and logistic model) to determine how various indicators of the poverty such as socioeconomic, demographic and social characteristics of households affect the poverty incidence in Jhang District. According to the survey conducted in 2016-17, 54% are below the Poverty Line in Jhang District. Depth and severity of poverty are 36% and 13% respectively. It is also noted that 16% of people are extremely poor whose income is Rs. 1515. The people of the area are found poorer compared to that of 33% in Punjab Province and 36% in Pakistan and 31% in the world. Education is the most significant factor that distinguishes the poor from the non-poor. Results of the logistic regression suggest that an increase in the landholding, livestock and total assets of the household have considerably decreasing the probability of being poor in the Jhang district. In the income regression analysis that size of household is the prime determinant of the per capita income of the household as a 1 % positive increase in the size of the household would decrease more than 1% per capita income of the household. It implies that the size of the household can add well to the level of poverty incidence in the Jhang district, Punjab. The results of logistic model shows that age of the households head, household size, household head is illiterate, household head is farmer, household head is daily wager or labor, residence in kacha(made of mud) house was positively and significantly correlated with the probability being poor while households satisfaction with education facilities and household have members in abroad for income purpose are negatively and significantly correlated with the probability of being poor.The results of the logistic regression suggest that an increase in the landholding, livestock and total assets of the household have considerably decreased the probability of being poor in the Jhang district. Moreover, the results show that an increase in the earners per household significantly reduce the probability of being poor in the Jhang district. Education plays an important role in the reduction of poverty and improving the socio-economic status of households. The results signify that educational attainment is significantly related to the likelihood of being poor in the Jhang district, Punjab.The ownership of the agriculture land and livestock is considered good for the reduction of the rural poverty in Pakistan. The estimated results of the logistic regression revealed that the coefficients of the landholding and livestock are negative and statistically significant in all four models. This indicates that an increase in the landholding and livestock of the households will reduce the probability of being poor in the Jhang district. The ownership of farming land and livestock have a significant impact on the reducing the probability that a household is poor. Similarly, the total assets of the households have also a negative and significant effect on the probability of being poor as the estimated coefficients of the total assets in all three models are negative and highly significant.Finally the dissertations conclude that it is important to examine these issues and address them on a long-term sustainable basis for all households at macro and micro level. Private individuals, industrialists, philanthropists, landlords, businessmen, and farmers all stakeholders collectively have to play a positive role in this regard. The primary and secondary data used in this study would help policymakers to design result-oriented programmes that would address poverty (Its magnitude and Correlates) in the study area.