Clean Energy Fuels Corp (CLNE) Fair Value & Analysis
Energy · US · Market cap $410M
Fair value as of: Jun 24, 2026
Analysis
Clean Energy Fuels Corp (CLNE) currently trades at $1.73, while our model-based Fair Value estimate is $1.70 — implying the stock looks roughly 1.7% overvalued today. We read business quality at 94/100 (high quality), in the Energy sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: medium).
About the company
Clean Energy Fuels Corp. offers natural gas as alternative fuels for vehicle fleets and related fueling solutions in the United States and Canada. It supplies renewable natural gas (RNG), compressed natural gas (CNG), and liquefied natural gas (LNG) for medium and heavy-duty vehicles; and provides operation and maintenance services for public and private vehicle fleet customer stations. The company also designs, builds, operates, and maintains vehicle fueling stations; and sells and services compressors and other equipment that are used in RNG production and fueling stations. In addition, it transports and sells CNG, RNG, and LNG through virtual natural gas pipelines and interconnects; sells U.S. federal, state, and local government credits, such as RNG as a vehicle fuel, including Renewable Identification Numbers and Low Carbon Fuel Standards credits; and obtains federal, state, and local credits, grants, and incentives. Further, the company focuses on developing, owning, and opera…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.