The phrase "able to predict more" is correct and usable in written English.
It can be used when discussing the capacity or capability to make additional predictions in a given context, such as data analysis or forecasting.
Example: "With the new algorithm, we are now able to predict more accurately the outcomes of various scenarios."
Alternatives: "capable of making further predictions" or "able to forecast additional outcomes."
The GCSEs will sort themselves out; we'll be able to predict more accurately in a couple of years.
Validation against the experiment data in the literature shows that the proposed model is able to predict more accurately the liner performance measured by the two-source method.
For diagnostic or prognostic problems, the question is whether these systems have been able to predict more accurately than human experts.
However, for un-notched specimens, where multiaxial loading effects come into play, no approach considered is able to predict more than 60% of fatigue data within a factor of ±3 of experimental life.
The focus then shifts to some recent advances in numerical methodology that are able to predict more accurately and efficiently the effective physical properties of multiphase materials with complex internal microstructures.
By tracking thousands of patterns of human interaction, the researchers hope to be able to predict more accurately the spread of pandemic flu and therefore provide healthcare agencies with the information to monitor and tackle outbreaks with the most cost-effective solutions.
By "mining" for likes, the software was able to predict personality more accurately than friends and family.
Similarly, if a company has long order backlogs, as Boeing does, it will be able to predict revenue more accurately, although the Boeing Dreamliner tribulations demonstrate that even "firm orders" don't automatically translate into future revenue.
"We are going to be able to predict much more accurately the long-term impact of the intervention," Hamdy says.
Finally, our method is able to predict significantly more non-canonical sites that are present within CLIPed regions than prior computational approaches.
As an application we show that the new metrics are able to predict software faults more effectively than existing metrics.
