Forest fires have become a major threat around the world, causing many negative impacts on human beings and forest ecosystems. Even though rapid climatic changes arising from high environmental pollution, greenhouse effects, etc. have caused this situation, a higher percentage of forest fires occur due to human activities. Therefore, to minimize the destruction caused by forest fires, the need to detect forest fires at their initial stage is needed. This paper proposes a model that can be used to detect forest fires at the initial stage using a wireless sensor network. Furthermore, to acquire more accurate fire detection, a machine learning regression model is proposed. Moreover, thorough attention is given to sensor node design and node placement in the forest to be fitted in the forest environment to minimize the damage and harmful effects caused by wild animals, weather conditions, etc. to the system.