Human trafficking is a severe abuse of human rights that entails the unlawful recruitment, transport, transfer, harboring, or receipt of individuals using force, deception, fraud, or coercion, all with the intent of exploiting them. This global issue affects millions of men, women and children, manifesting in various forms such as physical trafficking, labor trafficking, child trafficking, organ trafficking, and forced marriage. Victims are often concerned into commercial physical exploitation, forced labor in in-humane conditions, or the illegal trade of their organs. Children are especially vulnerable and many are exploited for labor or other illegal purposes. Governments and international organizations have enacted laws and conventions to combat human trafficking, emphasizing prevention, prosecution, and protection. Machine learning is a technology that is blooming in every field today. The techniques of machine learning can be used to decrease crime rate. The work described in the paper deploys distinct methodologies to identify the fraud jobs. In this paper we will develop different machine learning models to detect the fraud jobs that trap people for trafficking.