This paper presents the Probabilistic Topology-Aware Multi-Modal K-Nearest Neighbor (P-TAM-KNN) framework for assessing the resilience of California's Logging Truck Network (LTN). Two integrated contributions are made. First, Weibull reliability theory is embedded inside the KNN mechanism: the k structurally nearest bridge analogues identified by the Heterogeneous Network-Topology Distance (HNTD) are used as a distance-weighted sample for Weibull MLE, transforming every KNN query into a time-varying failure probability — the first use of KNN structural analogues as a Weibull parameter estimator. Second, the Supply Chain Resilience Index (SCRI) integrates the time-varying Weibull failure probability with corridor-level disruption severity and recovery capacity into a single risk metric, identifying US-101 as the most resilience-critical LTN corridor. Two-stream validation (KNN-Weibull parameters and Caltrans operational maintenance records) independently converges on US-101 as the highest-priority corridor for intervention.