Materialise NV (MTLS) Fair Value & Analysis
Technology · US · Market cap $390M
Fair value as of: Jun 24, 2026
Analysis
Materialise NV (MTLS) currently trades at $6.51, while our model-based Fair Value estimate is $2.90 — implying the stock looks roughly 55.5% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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
Materialise NV provides additive manufacturing and medical software tools, and 3D printing services in the Americas, Europe, Africa, and the Asia-Pacific. The company operates through three segments: Materialise Software, Materialise Medical, and Materialise Manufacturing. The Materialise Software segment offers proprietary software through programs and platforms that enable and enhance the functionality of 3D printers, and printing operations. Its software interfaces between various types of 3D printers; and various software applications and capturing technologies, including computer-aided design/computer-aided manufacturing packages and 3D scanners; a MES, software providers. This segment serves 3D printing machine manufacturers; production companies and contract manufacturers in automotive, aerospace, consumer goods, and hearing aid industries; and 3D printing service bureaus through its sales force, website, and third-party distributors. The Materialise Medical segment provides …
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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.