CELPIP Speaking Task 4: Making Predictions

I think the train will go away from the station soon, because it has a lot of smoke. Then the people on the right will walk to their work. Maybe they will be late. Also, I think more snow will come, because the sky is grey. Maybe some workers will come and take the wood for building. And the smoke will go to the buildings and the city will be dirty. I think after some time the yard will be quiet.

Several predictions with simple reasons, but will and maybe repeat and the links to the picture are thin.

Looking at this scene, I think a few things will happen fairly soon. First, the steam engine is already moving and producing a lot of smoke, so it will probably pull the freight cars out of the yard in the next few minutes. Second, the two people on the right seem to be heading somewhere in a hurry, so they are likely to cross the tracks once the train has passed. The sky is grey and heavy, which suggests that more snow might start falling later in the morning. Finally, those stacks of lumber look ready to be shipped, so I expect a crew could arrive to load them onto the next train.

Each prediction is tied to a visible clue and certainty is varied (will probably, are likely to, might, could).

Given what’s going on here, I’d say the most immediate change involves the locomotive. It’s clearly under steam, so within a minute or two it will almost certainly have pulled those freight cars out of view, and the smoke will start to drift across the buildings in the background. Once the line is clear, the two people walking on the right are likely to cross the tracks — they look as though they’re on their way to work and don’t want to be kept waiting in the cold. Judging by the low, grey sky, there’s a fair chance of more snow before noon, which might slow everything down. And with the lumber already stacked so neatly, I wouldn’t be surprised if a loading crew showed up later to get it onto the next train.

Sophisticated hedging (“there’s a fair chance”, “I wouldn’t be surprised if”), natural cause-and-effect and well-paced delivery.