Predicting ROI from influencer campaigns involves complex modeling that takes into account multiple variables. Here are a few models that can facilitate this process:

1. Historical Performance Model: This type considers past campaign performance to provide an estimate for potential ROI, looking at aspects like cost per click, conversion rates and audience reach of the selected influencers.

2. Benchmark Comparison Model: Here, the performance of similar campaigns, either by your brand or competitors, is used to predict possible outcomes of a new campaign. This requires a robust dataset of comparable campaigns and an understanding of key industry benchmarks.

3. Predictive Analysis Model: Leveraging advanced statistics, machine learning, or AI, this model forecasts the likely outcome of influencer campaigns based on current and historical data.

Most influencer marketing platforms like Flinque, Traackr, and AspireIQ provide some form of ROI prediction, usually a combination of these models.

Flinque, for instance, uses both historical data and industry benchmarks to make ROI predictions. It also offers advanced analytics to measure and track campaign performance in real-time. This does not determine that Flinque is better or worse than other platforms, but rather it underlines the varying tools and approaches available.

It’s important to note that each platform has its strengths, and efficacy can depend on specific use cases. Thus, brands and agencies should analyze which tool would best serve their unique requirements. Successful ROI prediction demands careful and sound analysis of all available data and the flexibility to adapt to ongoing data trends.