This study explores how brain metastases disrupt neural circuits, independently of tumor size or inflammation, and introduces a machine-learning approach to classify metastasis subtypes. Researchers used three preclinical mouse models of brain metastases: 482N1 (lung adenocarcinoma), E0771-BrM (breast cancer), and B16/F10-BrM (melanoma). Local field potential (LFP) recordings from cortical and hippocampal regions revealed that the 482N1 model caused the most pronounced electrophysiological disruptions, including reduced oscillatory power across delta (1–4 Hz), theta (4–12 Hz), and gamma (40–60 Hz) frequency bands. While all models impaired neural activity, 482N1 uniquely reduced inhibitory synapse density in peritumoral areas without affecting interneuron populations, highlighting a selective disruption of neuronal communication rather than global neuronal loss. Transcriptomic analysis revealed a molecular signature enriched in 482N1 models, including 51 upregulated genes related to neuronal communication, with Egr1 emerging as a critical regulator. This transcription factor was validated at the protein level in both mouse and human metastases and is implicated in synaptic plasticity and angiogenesis, suggesting a dual role in neural impairment and tumor-associated vascular changes. Electrophysiological and molecular findings demonstrated significant inter-model heterogeneity in the neural impact of metastases. To classify metastasis subtypes and detect tumors early, researchers employed machine learning on LFP spectral features. Principal component analysis (PCA) and generalized linear models (GLM) identified key electrophysiological signatures that distinguished metastasis models with 77% accuracy. These classifiers also detected tumor presence as early as seven days post-inoculation with 73% accuracy, emphasizing their diagnostic potential. Additionally, the 482N1 model demonstrated distinct calcium signaling activity in organotypic brain cultures, further supporting its superior impact on neural circuits. Whole exome sequencing identified 35 genetic alterations specific to the 482N1 model, which remain to be functionally characterized.