A flavoromics approach, integrating untargeted and targeted analyses, was applied to 18 lager beer samples to identify compounds that impact consumer liking. Cluster analysis of flavor liking scores revealed two distinct segments: one favoring lower flavor intensity and another favoring higher flavor intensity profiles. This study focused on the low-flavor-liking segment, using orthogonal partial least-squares regression to model the relationship between beer chemistry and consumer liking. Predictive models (R2Y ≥ 0.89, Q2 ≥ 0.82) were developed using untargeted liquid chromatography-mass spectrometry (LC/MS) and gas chromatography-mass spectrometry (GC/MS) profiling, complemented by targeted gas chromatography-tandem mass spectrometry (GC/MS/MS) analysis. Eleven compounds were identified as key predictors of liking, three positively and eight negatively correlated. Sensory difference testing and consumer evaluations confirmed that the addition of these predictive compounds significantly altered flavor perception and consumer preference in recombination beer models. By integrating targeted and untargeted approaches, this work demonstrates a methodology for identifying chemical contributors of flavor liking in lager beers.