Design Molecular classification is important for the diagnosis and prognosis of adrenocortical tumors (ACT). Transcriptome profiles separate adrenocortical adenomas ‘C2’ from carcinomas, and identify two groups of carcinomas ‘C1A’ and ‘C1B’, of poor and better prognosis respectively. However, many ACT cannot be profiled because of improper or absent freezing procedures, a mandatory requirement so far. The main aim was to determine transcriptome profiles on formalin-fixed paraffin-embedded (FFPE) samples, using the new 3’-end RNA-sequencing technology. A secondary aim was to demonstrate the ability of this technique to explore large FFPE archives, by focusing on the rare oncocytic ACT variants. Methods We included 131 ACT: a training cohort from Cochin hospital and an independent validation cohort from Wuerzburg hospital. The 3’ transcriptome was generated from FFPE samples using QuantSeq (Lexogen, Vienna, Austria) and NextSeq500 (Illumina, San Diego, CA, USA). Results In the training cohort, unsupervised clustering identified three groups: ‘C1A’ aggressive carcinomas (n = 28, 29%), ‘C1B’ more indolent carcinomas (n = 28, 29%), and ‘C2’ adenomas (n = 39, 41%). The prognostic value of FFPE transcriptome was confirmed in the validation cohort (5-year OS: 26% in ‘C1A’ (n = 26) and 100% in ‘C1B’ (n = 10), P = 0.003). FFPE transcriptome was an independent prognostic factor in a multivariable model including tumor stage and Ki-67 (OS HR: 7.5, P = 0.01). Oncocytic ACT (n = 19) did not form any specific cluster. Oncocytic carcinomas (n = 6) and oncocytic ACT of uncertain malignant potential (n = 4) were all in ‘C1B’. Conclusions The 3’ RNA-sequencing represents a convenient solution for determining ACT molecular class from FFPE samples. This technique should facilitate routine use and large retrospective studies.