A Case Study of Pakistan Determinants of Female Labour Force in South Asia women become part of the formal sector. Hence, the research question mainly focused on the education factor and how it impacts the LFP of women in Pakistan. As much as education is quintessential and a prerequisite for solving socio-economic problems, statistics on women’s education in South Asian countries are daunting. Access to education remains a concern where factors like social stigmas attached to women’s education, mobility, gender roles, and preference of educating boys amongst many stands in the way of girls’ education. To gauge what impact each level of education has on LFP in Pakistan, a Probit regression was done using variables of education, age, marriage(as in most cases, it acts as a barrier to continuing education and working for paid employment), sector of employment, location, and household size. The results were similar to most of the other literature findings that suggest a U-shaped relationship, meaning that individuals with little to no formal education have higher participation probability than the ones with primary and secondary levels of education. However, at tertiary levels of education, the participation probability is high. Married individuals, however, had lower participation rates than unmarried ones. This was then analyzed with the number of children a woman has, as childcare takes most of the women’s time at the cost of paid employment. It was found that the ones with tertiary levels of education have the least amount of childcare burden which could explain their higher participation rates. In addition, individuals working in an informal sector had higher participation probabilities than the ones in formal sector. For those residing in a rural, their participation probability is a lot lesser than the ones living in urban areas. In addition, the results also showed that with increasing age, the participation probability reduces which is in line with most of the other research findings. The household size was found to be insignificant for females in determining the decision to participate in the labour market Hence, to understand the overall pattern, other factors, for instance, income of the household, wages, mobility, childcare, type of occupation were analyzed. The research findings suggest a correlation between these factors i-e the higher the education level, the more the women are mobile and go out for work, engages in regular contracts, and earns higher wages. With each additional year of education, occupational gender segregation also reduces, suggesting that women could also work in other sectors apart from working in the primary sector as unpaid family help or on casual contracts. While correlation here does not imply causality, but it does highlight the positive externalities of education. Finally, more gender-equal education is 50