NMR Predict

Accurate prediction of 1H and 13C NMR spectra from a chemical structure.

Mnova NMR Predict calculates accurate and precise NMR chemical shifts using a novel procedure that combines several prediction engines in a constructive way. This method is called Ensemble NMR Prediction and uses several Machine Learning methods in combination with the well-knonwn Increments and HOSE-code algorithms developed by Modgraph Consultants. Prediction of chemical shifts of other nuclides is also available.

To complement the article about Ensemble NMR Prediction you can also read a blog post about 1H data here

Mnova NMR Predict: 45-day FREE trial

product_icon_download 1. Download

A plugin integrated in Mnova (separate license). No extra installer is required.

product_icon_install 2. Installation

Open Mnova and go to ‘Help/Get-Install Licenses’. Select ‘Evaluate’.

product_icon_license 3. License

Fill in the form to receive your trial license via e-mail.

Help & Resources

Please note that the new Mnova NMRPredict “Ensemble NMR Predictor” (Version ≥ 14) consists in two different licenses, Modgraph and Mestrelab Predictors



Make better decisions for your spectra faster!

  • Compute and display accurate chemical shifts for 1H, 13C, and other nuclides (11B, 15N,17O, 19F, 29Si, 31P) as well as J(HH), J(HF), J(HP), J(CF) and J(CP).
  • Predicted 1H-NMR spectra are synthesized using a rigorous quantum mechanism approach that takes into account strong coupling effects.
  • If the experimental spectrum is available, prediction will use the same experimental conditions (e.g. solvent and spectral properties: spectral width, spectrometer frequency, chemical shift reference, digital number of points, etc.)
  • Train your predictions by building your NMR databases from already assigned molecular structures.
  • Ability to drill-down user assigned 1H and 13C experimental data.
  • Each predicted value is accompanied by its confidence interval.

Academic, Government & Industrial


  • Pharmaceutical, chemical and food industries and QC environments
  • Research and NMR teaching in Academia
  • Suitable for individual users, research groups as well as large institutions and companies
Washington University
West Virginia University