Ammonia is currently widely used, but it can have adverse effects on human health. Therefore, the establishment of a highly sensitive and fast-responding ammonia sensor is necessary. A high-sensitivity nanoparticle-modified resistive ammonia sensor has been successfully fabricated. The resistance of the sensor decreases with increasing ammonia concentration and increases with increasing temperature. On the based of the measured current values and its trend, the predicted current values within the operating temperature and concentration range using linear regression analysis can be obtained. Additionally, another set of current values was estimated using the exponential function method based on the sensitivity values. By integrating the concept of the Kalman algorithm and the physical sensing mechanism of the device, we derived an advanced predictive current algorithm tailored specifically for sensor applications. This research has demonstrated a significant reduction in the measurement time and a substantial decrease in the gas consumption to ammonia sensing. As mentioned above, our study provides a new approach for sensor applications and model development.