Becker’s (1968) contribution to economics of crime has led the economists to dig out the causes and consequence of crimes. However, the menace of crimes adversely affects the overall social, economic and political health of a country. It is, therefore, imperative to identify the socio-economic determinants of crimes. The present work is an attempt to explore the socio-economic factors of crimes through conducting survey of the prisoners arrested against the charges of theft, robbery, dacoity and financial fraud in different prisons in Punjab. Other objectives include the elucidation of socio-economic and demographic characteristics of prisoners. The study was carried out in the Punjab because it has 53 percent of the country’s population, 60 percent of the total reported crimes and 67 percent of the prison population of Pakistan. A well-structured questionnaire was designed to interview prisoners and cluster sampling technique was used to draw the representative sample. A survey of 967 prisoners, regardless of their legal status, was conducted in 30 prisons in Punjab. The survey revealed that 50 percent prisoners were arrested for the indictment of theft, 21 percent were kept in the prisons due to robbery, 17 percent were arrested for dacoity, 11 percent were financial fraud offenders and only 1 percent was of the prisoners were arrested due to other crimes. Among prisoners arrested for theft, 10 percent held unemployment responsible for their involvement and 41 percent told that due to poverty they had committed theft. However, 6 percent claimed that due to family issues they had committed theft and 41 percent told different reasons of their participation in theft. Similarly, among prisoners arrested against the charges of robbery, 31 percent held poverty, 16 percent blamed unemployment, 7 percent told family background and 46 percent stated different reasons of their involvement in robbery. Prisoners of dacoity alleged poverty (26 percent), unemployment (8 percent), family background (10 percent) and different reasons (56 percent) of their detention. Only 8 percent of the financial fraud prisoners held unemployment, poverty, family background and keeping up with the joneses responsible of their involvement in financial fraud; however, the remaining 92 percent explained several reasons of their participation in financial fraud. Depending upon the nature of data, binary logistic regression technique was used to find out the relationship between socio- economic determinants and crimes. The results of binary logistic regression of the relationship between theft and socioeconomic determinants without including prison population background characteristics revealed that unemployment and family background had insignificant relationship with theft whereas poverty and other reasons had significant relationship with theft. Similar results were found when prison population background characteristics were included in the model. The relationship between robbery and socioeconomic determinants without prisoner background characteristics explained that unemployment and other reasons had significant relationship with robbery while poverty and family issues had insignificant relationship with robbery. On the other hand, by incorporating the prisoner background characteristics, only unemployment had significant relationship with robbery. The relationship between dacoity and socioeconomic determinants without prisoner background characteristics showed that only family issues had significant relationship with dacoity. The inclusion of prisoner background characteristics in the model resulted in insignificant relationship with unemployment, poverty, family background and other reasons. However, financial fraud had significant relationship with unemployment, poverty and other reasons while family background had insignificant relationship. Similar estimates were obtained when prisoner background characteristics were included in the model. The findings revealed that socio-economic and demographic characteristics provoke individuals to get involved in theft, robbery, dacoity and financial fraud in Punjab.