Agriculture plays an important role in Indian economy and development. But due to unfamiliar weather conditions and attacks by different microorganisms, crops are getting infected. This causes a huge loss to the farmer and impacts the economy and food security. Therefore, determining crop diseases at an early stage is very important to prevent losses, maintain quality and increase crop productivity. However, due to a lack of knowledge and unavailability of resources, immediate identification of diseases through visual monitoring is difficult. To overcome this problem, we need a proper monitoring system that helps to predict the type of infection or disease present. This information can be valuable for farmers to take appropriate measures to prevent and control the spread of diseases.Many researchers have been working in this direction for decades. This survey paper provides a comprehensive overview of the current state of research in the field of plant disease prediction, focusing on various techniques, methodologies, and advancements. The survey paper begins by discussing existing plant disease prediction methods, different machine learning -based models, various technologies used in them, their performance, and challenges associated with plant disease prediction. Furthermore, the survey paper includes the future possibilities of the development in the domain of plant disease prediction. The paper concludes by highlighting why it is important to predict plant diseases accurately. If done well, accurate prediction can help farmers grow food in an environmentally friendly manner and ensure there is enough food for everyone around the world.