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The ultrasound-assisted extraction (UAE) method was optimized to extract bioactive compounds from Licaria armeniaca tissues. Extraction time, solid–liquid ratio (m/v), and ethanol percentage were investigated using a central composite rotational design and response surface methodology (RSM). Antioxidant activity (DPPH) and total phenolic content (TPC) served as the response variables. Most efficient extraction conditions were obtained for leaves (64.88% ethanol, 26.07 min, 6.23% m/v; R2 = 0.93) and thin branches (73.81% ethanol, 31.34 min, 11% m/v; R2 = 0.74). For thick branches, no significant predictive model was obtained, and optimal points were defined based on the best observed TPC and DPPH results (50% ethanol, 35 min, 11% m/v). The optimized extracts were analyzed by liquid chromatography–tandem mass spectrometry associated with molecular networking, GNPS (Global Natural Products Social Molecular Network) library searching, and machine learning tools. Metabolomic profiling indicated that leaves contained mainly alkaloids (46.34%), amino acids and peptides (19.51%), and shikimate derivatives and phenylpropanoids (12.20%). Thin branches showed predominance of alkaloids (35.97%), amino acids and peptides (20.86%), and carbohydrates (12.23%), while thick branches contained alkaloids (46.34%), amino acids and peptides (25.00%), and fatty acids (14.26%). Additionally, the extracts displayed significant cytotoxic activity against cancer cell lines of AGP-01 (malignant gastric ascites), AHOL (Human glioblastoma) and A549 (lung cancer) with IC50 values less than 50 μg/mL.