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The shelf-life of fresh-cut lettuce after storage is limited by several factors that affect its quality and lead to consumer rejection. Different metabolic events occur after cutting as an abiotic stress response. This study aims to explore the metabolome of iceberg lettuce and to understand the changes related to storage time and genetics applying an untargeted metabolomics approach. Two cultivars with different browning susceptibility, fast-browning (FB) and slow-browning (SB), were analyzed by UPLC-ESI-QTOF-MS just after cutting (d0) and after five days of storage (d5). Extraction, metabolic profiling, and data-pretreatment procedures were optimized to obtain a robust and reliable data set. Preliminary principal component analysis and hierarchical cluster analysis of the full dataset [around 8551 extracted, aligned and filtered molecular features (MFs)] showed a clear separation between the different samples (FB-d0, FB-d5, SB-d0, and SB-d5), highlighting a clear storage time-dependent effect. After statistical analysis applying Student’s t test, 536 MFs were detected as significantly different between d0 and d5 of storage in FB and 633 in SB. Some of them (221) were common to both cultivars. Out of these significant compounds, 22 were tentatively identified by matching their molecular formulae with those previously reported in the literature. Five families of metabolites were detected: amino acids, phenolic compounds, sesquiterpene lactones, fatty acids, and lysophospholipids. All compounds showed a clear trend to decrease at d5 except phenolic compounds that increased after storage. The untargeted metabolomics analysis is a powerful tool for characterizing the changes on lettuce metabolome associated with cultivar and especially with storage time. Some families of compounds affected by storage time were reported to be closely related to quality loss.