For predicting you can use following :
y = net(x); % x contains input data and y is predicted data
If you want to create plot of prediction you can use plot command.
For general NN code see following:
x = input;
t = target;
trainFcn = 'trainlm';
hiddenLayerSize = [10 15 10]; % 3hiddenlayers of with different no. of neurons
net = feedforwardnet(hiddenLayerSize,trainFcn);
% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
[net,tr] = train(net,x,t);
% Test the Network
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y)
view(net)
% Uncomment these lines to enable various plots.
%figure, plotperform(tr)
%figure, plottrainstate(tr)
%figure, ploterrhist(e)
%figure, plotregression(t,y)
%figure, plotfit(net,x,t)
