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Enerflex Ltd (EFXT) Fair Value & Analysis

Energy · US · Market cap $3.2B

Price$25.25
Fair Value$16.07
Upside-36.4%
Quality95/100
Evidence: High Range $12.06 – $20.09

Analysis

Enerflex Ltd (EFXT) currently trades at $25.25, while our model-based Fair Value estimate is $16.07 — implying the stock looks roughly 36.4% overvalued today. We read business quality at 95/100 (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: high).

About the company

Enerflex Ltd. offers modular natural gas, power technology, and treated water solutions in North America, Latin America, and the Eastern Hemisphere. The company's portfolio includes compression, processing, cryogenic, treated water solutions, and energy infrastructure portfolio includes energy infrastructure solutions under contract for natural gas processing, compression, and treated water equipment. It also provides contract operations services that includes trained personnel, equipment, tools, materials, and supplies to meet natural gas needs, electric power, and produced water needs as well as designing, sourcing, installing, operating, servicing, repairing, and maintaining equipment. In addition, the company offers after-market services products, such as delivers comprehensive mechanical services to client partners, including parts distribution; operations and maintenance solutions; equipment optimization and maintenance programs; manufacturer warranties; exchange components; l…

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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.