The corrosion and deterioration of iron cultural relics in museum collections, under the coupled effects of multiple factors, pose a severe challenge for cultural heritage conservation. This study systematically quantified the synergistic corrosion effects of environmental factors, including temperature, humidity, SO₂, NO₂, O₃, HCOOH, and Cl- on iron cultural relics through simulated exposure experiments. A hybrid prediction model was developed based on a Random Forest (RF)-Long Short-Term Memory (LSTM) network. This study introduced a “Corrosion Index (IP)” to correlate environmental stress with the condition of cultural relics. By combining feature engineering of a temperature-humidity interaction term (T_RH) and a pollutant synergy term (SO₂_RH), the approach enabled accurate time-segmented prediction of the corrosion rate (60-day prediction R²=0.940). Feature importance analysis identified Cl- as the core risk factor (with a long-term contribution of 0.32), while the temperature-humidity synergy (T_RH) consistently dominated the corrosion process (contribution of 0.28 ± 0.03). Based on corrosion kinetic thresholds, a four-tier risk classification model was established, and a graphical user interface (GUI) supporting real-time assessment was developed, providing technical support for the preventive conservation of museum iron art culture relics.