Cervical remodeling during pregnancy is a critical process that, if untimely, can lead to complications such as preterm birth (PTB). This study introduces a novel multi-parametric approach combining non-invasive imaging modalities to quantify cervical tissue changes during pregnancy and postpartum in a murine model. By integrating ultrasound-based measurements of cervical length, photoacoustic imaging of the collagen-to-water ratio, and elastography for tissue elasticity alongside histological assessments, this method provides a comprehensive evaluation of cervical remodeling. The findings reveal that combining these parameters significantly improves the accuracy of gestational age prediction compared to individual measurements, with a tri-parametric model achieving 85.3% prediction accuracy compared to 65.4% accuracy with histological analysis alone. This approach not only enhances the understanding of cervical remodeling but also holds potential as a minimally invasive, point-of-care diagnostic tool for early detection of cervical ripening and PTB risk. Ultimately, these advancements could inform clinical strategies for pregnancy management and labor induction, improving maternal and neonatal outcomes.