EVI Industries, Inc (EVI) Fair Value & Analysis
Industrials · US · Market cap $205M
Fair value as of: Jun 24, 2026
Analysis
EVI Industries, Inc (EVI) currently trades at $15.25, while our model-based Fair Value estimate is $12.24 — implying the stock looks roughly 19.7% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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
EVI Industries, Inc., through its subsidiaries, engages in the distribution, sale, rental, and lease of commercial and industrial laundry and dry-cleaning equipment. It sells and/or leases commercial laundry equipment, specializing in washing, drying, finishing, material handling, water heating, power generation, and water reuse applications. The company offers washroom, finishing, material handling, and mechanical equipment, such as washers and dryers, tunnel systems, and vended machines; finishing equipment, such as sheet feeders, flatwork ironers, automatic sheet folders, and stackers; and material handling equipment, including conveyor and rail systems. It also provides mechanical equipment, such as boilers, hot water/steam systems, air compressors, and power generation products, as well as water purification, reuse, and recycling systems used for temperature control, heating, pressing and de-wrinkling, sterilization, product sealing, and other purposes in the laundry and dry cl…
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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.