The fire detection plays a critical role in the maintenance of public security. Previous approaches of early fire warning, based on smoke or temperature response must be set in the proximity of a fire. They cannot provide the additional information of fire location or size and are susceptible to complicated situations. It is still a big challenge to make rapid and accurate early fire warning in precombustion because of the lack of reliable alarm signals. Herein, a precursor molecular sensor (PMS) is designed and synthesized that can present the chemical structure transformation to form phthalocyanines (Pcs) and release a color change signal at about 180 °C, learning from the plant chlorophyll metabolism. Further, the PMS is assembled to an early fire warning component (EWC) and an intelligent image recognition algorithm is introduced for unburned fire detection. The EWC generates a colorful alarm within 20 s at 275 °C. Therefore, the facile PMS provides a reliable real‐time monitoring strategy to the early fire warning detection in precombustion. A bioinspired color changing molecular sensor is designed to achieve early fire detection based on transformation of phthalonitrile to phthalocyanine, learning from the plant chlorophyll metabolism. An intelligent image recognition algorithm is applied and the sensor generates colorful alarm within 20 s at 275 °C. This study provides a reliable real‐time monitoring strategy to the early fire detection in precombustion.